diff --git a/ci/scripts/test_imports.sh b/ci/scripts/test_imports.sh
index 16a4f652..5f310b69 100644
--- a/ci/scripts/test_imports.sh
+++ b/ci/scripts/test_imports.sh
@@ -19,3 +19,4 @@ test_import "aws"               "import dask_cloudprovider.aws"
 test_import "azure"             "import dask_cloudprovider.azure"
 test_import "digitalocean"      "import dask_cloudprovider.digitalocean"
 test_import "gcp"               "import dask_cloudprovider.gcp"
+test_import "openstack"         "import dask_cloudprovider.openstack"
\ No newline at end of file
diff --git a/dask_cloudprovider/cloudprovider.yaml b/dask_cloudprovider/cloudprovider.yaml
index aa99b102..932bea1f 100755
--- a/dask_cloudprovider/cloudprovider.yaml
+++ b/dask_cloudprovider/cloudprovider.yaml
@@ -118,3 +118,18 @@ cloudprovider:
     image: "ubuntu-20.04" # Operating System image to use
     docker_image: "daskdev/dask:latest" # docker image to use
     bootstrap: true # It is assumed that the OS image does not have Docker and needs bootstrapping. Set this to false if using a custom image with Docker already installed.
+
+  openstack:
+    region: "RegionOne" # The name of the region where resources will be allocated in OpenStack. List available regions using: `openstack region list`.
+    size: null # Openstack flavors define the compute, memory, and storage capacity of computing instances. List available flavors using: `openstack flavor list`
+    auth_url: null # The authentication URL for the OpenStack Identity service (Keystone). Example: https://cloud.example.com:5000
+    application_credential_id: null # The application credential id created in OpenStack. Create application credentials using: openstack application credential create
+    application_credential_secret: null # The secret associated with the application credential ID for authentication.
+    auth_type: "v3applicationcredential" # The type of authentication used, typically "v3applicationcredential" for using OpenStack application credentials.
+    network_id: null # The unique identifier for the internal/private network in OpenStack where the cluster VMs will be connected. List available networks using: `openstack network list`
+    image: null # The OS image name or id to use for the VM. List available images using: `openstack image list` 
+    keypair_name: null # The name of the SSH keypair used for instance access. Ensure you have created a keypair or use an existing one. List available keypairs using: `openstack keypair list`
+    security_group: null # The security group name that defines firewall rules for instances.  List available security groups using: `openstack security group list`
+    external_network_id: null # The ID of the external network used for assigning floating IPs. List available external networks using: `openstack network list --external`
+    create_floating_ip: false # Specifies whether to assign a floating IP to each instance, enabling external access. Set to `True` if external connectivity is needed.
+    docker_image: "daskdev/dask:latest" # docker image to use
\ No newline at end of file
diff --git a/dask_cloudprovider/openstack/__init__.py b/dask_cloudprovider/openstack/__init__.py
new file mode 100644
index 00000000..91ca9fe0
--- /dev/null
+++ b/dask_cloudprovider/openstack/__init__.py
@@ -0,0 +1 @@
+from .instances import OpenStackCluster
diff --git a/dask_cloudprovider/openstack/instances.py b/dask_cloudprovider/openstack/instances.py
new file mode 100644
index 00000000..903a4a16
--- /dev/null
+++ b/dask_cloudprovider/openstack/instances.py
@@ -0,0 +1,372 @@
+import asyncio
+import dask
+
+from dask_cloudprovider.generic.vmcluster import (
+    VMCluster,
+    VMInterface,
+    SchedulerMixin,
+    WorkerMixin,
+)
+
+from distributed.core import Status
+
+try:
+    from openstack import connection
+except ImportError as e:
+    msg = (
+        "Dask Cloud Provider OpenStack requirements are not installed.\n\n"
+        "Please pip install as follows:\n\n"
+        '  pip install "openstacksdk" '
+    )
+    raise ImportError(msg) from e
+
+
+class OpenStackInstance(VMInterface):
+    def __init__(
+        self,
+        cluster,
+        config,
+        region: str = None,
+        size: str = None,
+        image: str = None,
+        docker_image: str = None,
+        env_vars: str = None,
+        extra_bootstrap: str = None,
+        **kwargs,
+    ):
+        super().__init__(**kwargs)
+        self.instance = None
+        self.cluster = cluster
+        self.config = config
+        self.region = region
+        self.size = size
+        self.image = image
+        self.env_vars = env_vars
+        self.bootstrap = True
+        self.docker_image = docker_image
+        self.extra_bootstrap = extra_bootstrap
+
+    async def create_vm(self):
+        conn = connection.Connection(
+            region_name=self.region,
+            auth_url=self.config["auth_url"],
+            application_credential_id=self.config["application_credential_id"],
+            application_credential_secret=self.config["application_credential_secret"],
+            compute_api_version="2",
+            identity_interface="public",
+            auth_type="v3applicationcredential",
+        )
+
+        self.instance = conn.create_server(
+            name=self.name,
+            image=self.image,
+            flavor=self.size,  # Changed 'flavor_id' to 'flavor'
+            key_name=self.config["keypair_name"],  # Add the keypair name here
+            nics=[
+                {"net-id": self.config["network_id"]}
+            ],  # Changed from 'networks' to 'nics'
+            userdata=self.cluster.render_process_cloud_init(self),
+            security_groups=[self.config["security_group"]],
+        )
+
+        # Wait for the instance to be up and running
+        while self.instance.status.lower() != "active":
+            await asyncio.sleep(0.1)
+            self.instance = conn.compute.get_server(self.instance.id)
+
+        # Retrieve the internal IP address
+        self.internal_ip = await self.get_internal_ip(conn)
+
+        # Check if a floating IP should be created and assigned
+        if self.config.get("create_floating_ip", False):
+            self.external_ip = await self.create_and_assign_floating_ip(conn)
+        else:
+            self.external_ip = await self.get_external_ip(conn)
+
+        self.cluster._log(
+            f"{self.name}\n\tInternal IP: {self.internal_ip}\n\tExternal IP: "
+            f"{self.external_ip if self.external_ip else 'None'}"
+        )
+        return self.internal_ip, self.external_ip
+
+    async def get_internal_ip(self, conn):
+        """Fetch the internal IP address from the OpenStack instance."""
+        instance = conn.compute.get_server(self.instance.id)
+        for network in instance.addresses.values():
+            for addr in network:
+                if addr["OS-EXT-IPS:type"] == "fixed":
+                    return addr["addr"]
+        return None
+
+    async def get_external_ip(self, conn):
+        """Fetch the external IP address from the OpenStack instance, if it exists."""
+        instance = conn.compute.get_server(self.instance.id)
+        for network in instance.addresses.values():
+            for addr in network:
+                if addr["OS-EXT-IPS:type"] == "floating":
+                    return addr["addr"]
+        return None
+
+    async def create_and_assign_floating_ip(self, conn):
+        """Create and assign a floating IP to the instance."""
+        try:
+            # Create a floating IP
+            floating_ip = await self.cluster.call_async(
+                conn.network.create_ip,
+                floating_network_id=self.config["external_network_id"],
+            )
+
+            # Assign the floating IP to the server
+            await self.cluster.call_async(
+                conn.compute.add_floating_ip_to_server,
+                server=self.instance.id,
+                address=floating_ip.floating_ip_address,
+            )
+
+            return floating_ip.floating_ip_address
+        except Exception as e:
+            self.cluster._log(f"Failed to create or assign floating IP: {str(e)}")
+            return None
+
+    async def destroy_vm(self):
+        conn = connection.Connection(
+            region_name=self.region,
+            auth_url=self.config["auth_url"],
+            application_credential_id=self.config["application_credential_id"],
+            application_credential_secret=self.config["application_credential_secret"],
+            compute_api_version="2",
+            identity_interface="public",
+            auth_type="v3applicationcredential",
+        )
+
+        # Handle floating IP disassociation and deletion if applicable
+        if self.config.get(
+            "create_floating_ip", False
+        ):  # Checks if floating IPs were configured to be created
+            try:
+                # Retrieve all floating IPs associated with the instance
+                floating_ips = conn.network.ips(port_id=self.instance.id)
+                for ip in floating_ips:
+                    # Disassociate and delete the floating IP
+                    conn.network.update_ip(ip, port_id=None)
+                    conn.network.delete_ip(ip.id)
+                    self.cluster._log(f"Deleted floating IP {ip.floating_ip_address}")
+            except Exception as e:
+                self.cluster._log(
+                    f"Failed to clean up floating IPs for instance {self.name}: {str(e)}"
+                )
+                return  # Exit if floating IP cleanup fails
+
+        # Then, attempt to delete the instance
+        try:
+            instance = conn.compute.get_server(self.instance.id)
+            if instance:
+                await self.cluster.call_async(conn.compute.delete_server, instance.id)
+                self.cluster._log(f"Terminated instance {self.name}")
+            else:
+                self.cluster._log(f"Instance {self.name} not found or already deleted.")
+        except Exception as e:
+            self.cluster._log(f"Failed to terminate instance {self.name}: {str(e)}")
+
+    async def start_vm(self):
+        # Code to start the instance
+        pass  # Placeholder to ensure correct indentation
+
+    async def stop_vm(self):
+        # Code to stop the instance
+        pass  # Placeholder to ensure correct indentation
+
+
+class OpenStackScheduler(SchedulerMixin, OpenStackInstance):
+    """Scheduler running on an OpenStack Instance."""
+
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+
+    async def start(self):
+        await self.start_scheduler()
+        self.status = Status.running
+
+    async def start_scheduler(self):
+        self.cluster._log(
+            f"Launching cluster with the following configuration: "
+            f"\n  OS Image: {self.image} "
+            f"\n  Flavor: {self.size} "
+            f"\n  Docker Image: {self.docker_image} "
+            f"\n  Security Group: {self.config['security_group']} "
+        )
+        self.cluster._log("Creating scheduler instance")
+        self.internal_ip, self.external_ip = await self.create_vm()
+
+        # Choose the IP based on the access type configuration
+        if self.config.get("create_floating_ip", True):
+            # If public access is required and a floating IP is created
+            self.address = f"{self.cluster.protocol}://{self.external_ip}:{self.port}"
+        else:
+            # Use internal IP if no external access is configured
+            self.address = f"{self.cluster.protocol}://{self.internal_ip}:{self.port}"
+
+        await self.wait_for_scheduler()
+
+        # Storing IPs for cluster-wide use, if necessary
+        self.cluster.scheduler_internal_ip = self.internal_ip
+        self.cluster.scheduler_external_ip = self.external_ip
+        self.cluster.scheduler_port = self.port
+
+
+class OpenStackWorker(WorkerMixin, OpenStackInstance):
+    """Worker running on a OpenStack Instance."""
+
+
+class OpenStackCluster(VMCluster):
+    """Cluster running on Openstack VM Instances
+
+    This cluster manager constructs a Dask cluster running on generic Openstack cloud
+
+    When configuring your cluster you may find it useful to install the 'python-openstackclient'
+    client for querying the Openstack APIs for available options.
+
+    https://github.com/openstack/python-openstackclient
+
+    Parameters
+    ----------
+
+    region: str
+        The name of the region where resources will be allocated in OpenStack.
+        Typically set to 'default' unless specified in your cloud configuration.
+
+        List available regions using: `openstack region list`.
+    auth_url: str
+        The authentication URL for the OpenStack Identity service (Keystone).
+        Example: https://cloud.example.com:5000
+    application_credential_id: str
+         The application credential id created in OpenStack.
+
+         Create application credentials using: openstack application credential create
+    application_credential_secret: str
+        The secret associated with the application credential ID for authentication.
+    auth_type: str
+        The type of authentication used, typically "v3applicationcredential" for
+        using OpenStack application credentials.
+    network_id: str
+        The unique identifier for the internal/private network in OpenStack where the cluster
+        VMs will be connected.
+
+        List available networks using: `openstack network list`
+    image: str
+        The OS image name or id to use for the VM. Dask Cloudprovider will boostrap Ubuntu
+        based images automatically. Other images require Docker and for GPUs
+        the NVIDIA Drivers and NVIDIA Docker.
+
+        List available images using: `openstack image list`
+    keypair_name: str
+        The name of the SSH keypair used for instance access. Ensure you have created a keypair
+        or use an existing one.
+
+        List available keypairs using: `openstack keypair list`
+    security_group: str
+        The security group name that defines firewall rules for instances.
+
+        The default is `default`. Please ensure the follwing accesses are configured:
+            - egress 0.0.0.0/0 on all ports for downloading docker images and general data access
+            - ingress <internal-cidr>/8 on all ports for internal communication of workers
+            - ingress 0.0.0.0/0 on 8786-8787 for external accessibility of the dashboard/scheduler
+            - (optional) ingress 0.0.0.0./0 on 22 for ssh access
+
+        List available security groups using: `openstack security group list`
+    create_floating_ip: bool
+        Specifies whether to assign a floating IP to each instance, enabling external
+        access. Set to `True` if external connectivity is needed.
+    external_network_id: str
+        The ID of the external network used for assigning floating IPs.
+
+        List available external networks using: `openstack network list --external`
+    n_workers: int (optional)
+        Number of workers to initialise the cluster with. Defaults to ``0``.
+    worker_module: str
+        The Python module to run for the worker. Defaults to ``distributed.cli.dask_worker``
+    worker_options: dict
+        Params to be passed to the worker class.
+        See :class:`distributed.worker.Worker` for default worker class.
+        If you set ``worker_module`` then refer to the docstring for the custom worker class.
+    scheduler_options: dict
+        Params to be passed to the scheduler class.
+        See :class:`distributed.scheduler.Scheduler`.
+    env_vars: dict
+        Environment variables to be passed to the worker.
+    extra_bootstrap: list[str] (optional)
+        Extra commands to be run during the bootstrap phase.
+    docker_image: string (optional)
+        The Docker image to run on all instances.
+
+        This image must have a valid Python environment and have ``dask`` installed in order for the
+        ``dask-scheduler`` and ``dask-worker`` commands to be available. It is recommended the Python
+        environment matches your local environment where ``OpenStackCluster`` is being created from.
+
+        For GPU instance types the Docker image much have NVIDIA drivers and ``dask-cuda`` installed.
+
+        By default the ``daskdev/dask:latest`` image will be used.
+
+    Example
+    --------
+
+    >>> from dask_cloudprovider.openstack import OpenStackCluster
+    >>> cluster = OpenStackCluster(n_workers=1)
+    Launching cluster with the following configuration:
+        OS Image: ubuntu-22-04
+        Flavor: 4vcpu-8gbram-50gbdisk
+        Docker Image: daskdev/dask:latest
+        Security Group: all-open
+    Creating scheduler instance
+        dask-9b85a5f8-scheduler
+                Internal IP: 10.0.30.148
+                External IP: None
+    Waiting for scheduler to run at 10.0.30.148:8786
+    Scheduler is running
+    Creating worker instance
+
+    >>> from dask.distributed import Client
+    >>> client = Client(cluster)
+
+    >>> import dask.array as da
+    >>> arr = da.random.random((1000, 1000), chunks=(100, 100))
+    >>> arr.mean().compute()
+
+    >>> client.close()
+    >>> cluster.close()
+    Terminated instance dask-07280176-worker-319005a2
+    Terminated instance dask-07280176-scheduler
+    """
+
+    def __init__(
+        self,
+        region: str = None,
+        size: str = None,
+        image: str = None,
+        docker_image: str = None,
+        debug: bool = False,
+        bootstrap: bool = True,
+        **kwargs,
+    ):
+        self.config = dask.config.get("cloudprovider.openstack", {})
+        self.scheduler_class = OpenStackScheduler
+        self.worker_class = OpenStackWorker
+        self.debug = debug
+        self.bootstrap = (
+            bootstrap if bootstrap is not None else self.config.get("bootstrap")
+        )
+        self.options = {
+            "cluster": self,
+            "config": self.config,
+            "region": region if region is not None else self.config.get("region"),
+            "size": size if size is not None else self.config.get("size"),
+            "image": image if image is not None else self.config.get("image"),
+            "docker_image": docker_image or self.config.get("docker_image"),
+        }
+        self.scheduler_options = {**self.options}
+        self.worker_options = {**self.options}
+
+        if "extra_bootstrap" not in kwargs:
+            kwargs["extra_bootstrap"] = self.config.get("extra_bootstrap")
+
+        super().__init__(debug=debug, **kwargs)
diff --git a/dask_cloudprovider/openstack/tests/test_instances.py b/dask_cloudprovider/openstack/tests/test_instances.py
new file mode 100644
index 00000000..eae815bf
--- /dev/null
+++ b/dask_cloudprovider/openstack/tests/test_instances.py
@@ -0,0 +1,72 @@
+import pytest
+import dask
+from dask_cloudprovider.openstack.instances import OpenStackCluster
+from dask.distributed import Client
+from distributed.core import Status
+
+# Optional: Skips tests if OpenStack credentials are not set
+
+
+async def skip_without_credentials(config):
+    if (
+        config.get("auth_url") is None
+        or config.get("application_credential_secret") is None
+    ):
+        pytest.skip(
+            """
+        You must configure OpenStack credentials to run this test.
+
+        Set this in your config file or environment variables:
+
+        # cloudprovider.yaml
+        cloudprovider:
+          openstack:
+            auth_url: "your_auth_url"
+            application_credential_id: "your_app_cred_id"
+            application_credential_secret: "your_app_cred_secret"
+        """
+        )
+
+
+@pytest.fixture
+async def config():
+    return dask.config.get("cloudprovider.openstack", {})
+
+
+@pytest.fixture
+@pytest.mark.external
+async def cluster(config):
+    await skip_without_credentials(config)
+
+    async with OpenStackCluster(asynchronous=True) as cluster:
+        yield cluster
+
+
+@pytest.mark.asyncio
+async def test_init():
+    cluster = OpenStackCluster(asynchronous=True)
+    assert cluster.status == Status.created
+
+
+@pytest.mark.asyncio
+@pytest.mark.timeout(600)
+async def test_create_cluster(cluster):
+    assert cluster.status == Status.running
+    cluster.scale(1)
+    await cluster
+    assert len(cluster.workers) == 1
+
+    async with Client(cluster, asynchronous=True) as client:
+
+        def inc(x):
+            return x + 1
+
+        assert await client.submit(inc, 10).result() == 11
+
+
+@pytest.mark.asyncio
+async def test_get_cloud_init():
+    cloud_init = OpenStackCluster.get_cloud_init(
+        docker_args="--privileged",
+    )
+    assert " --privileged " in cloud_init
diff --git a/dask_cloudprovider/tests/test_imports.py b/dask_cloudprovider/tests/test_imports.py
index e9ab7b4d..3dc42e66 100644
--- a/dask_cloudprovider/tests/test_imports.py
+++ b/dask_cloudprovider/tests/test_imports.py
@@ -24,3 +24,5 @@ def test_import_exceptions():
         from dask_cloudprovider import GCPCluster  # noqa
     with pytest.raises(ImportError):
         from dask_cloudprovider import DropletCluster  # noqa
+    with pytest.raises(ImportError):
+        from dask_cloudprovider import OpenStackCluster  # noqa
diff --git a/doc/source/index.rst b/doc/source/index.rst
index c2e57968..74d2a661 100644
--- a/doc/source/index.rst
+++ b/doc/source/index.rst
@@ -70,6 +70,7 @@ this code.
     gcp.rst
     azure.rst
     hetzner.rst
+    openstack.rst
 
 .. toctree::
     :maxdepth: 2
diff --git a/doc/source/installation.rst b/doc/source/installation.rst
index b953cbd6..f4994435 100644
--- a/doc/source/installation.rst
+++ b/doc/source/installation.rst
@@ -16,7 +16,8 @@ You can also restrict your install to just a specific cloud provider by giving t
    $ pip install dask-cloudprovider[azure]  # or
    $ pip install dask-cloudprovider[azureml]  # or
    $ pip install dask-cloudprovider[digitalocean]  # or
-   $ pip install dask-cloudprovider[gcp]
+   $ pip install dask-cloudprovider[gcp]  # or
+   $ pip install dask-cloudprovider[openstack]
 
 Conda
 -----
diff --git a/doc/source/openstack.rst b/doc/source/openstack.rst
new file mode 100644
index 00000000..cb0a743d
--- /dev/null
+++ b/doc/source/openstack.rst
@@ -0,0 +1,75 @@
+Openstack
+============
+
+.. currentmodule:: dask_cloudprovider.openstack
+
+.. autosummary::
+   OpenStackCluster
+
+Overview
+--------
+
+Authentication
+^^^^^^^^^^^^^^
+
+To authenticate with the OpenStack Identity service (Keystone) 
+
+1) Get your Authentication URL (auth_url) for OpenStack Identity service (Keystone) and put it in your Dask configuration at ``cloudprovider.openstack.auth_url``.
+
+2) Get your `region <https://docs.openstack.org/python-openstackclient/latest/cli/command-objects/region.html>`_ and put it in your Dask configuration at ``cloudprovider.openstack.region``.
+    .. code-block:: console
+
+        $ openstack region list
+        +-----------+---------------+-------------+
+        | Region    | Parent Region | Description |
+        +-----------+---------------+-------------+
+        | RegionOne | None          |             |
+        +-----------+---------------+-------------+
+
+3) Generate an  `application credential <https://docs.openstack.org/keystone/latest/user/application_credentials.html>`_.
+
+    .. code-block:: console
+
+        $ openstack application credential create dask --unrestricted
+        +--------------+----------------------------------------------------------------------------------------+
+        | Field        | Value                                                                                  |
+        +--------------+----------------------------------------------------------------------------------------+
+        | description  | None                                                                                   |
+        | expires_at   | None                                                                                   |
+        | id           | 0a0372dbedfb4e82ab66449c3316ef1e                                                       |
+        | name         | dask                                                                             |
+        | project_id   | e99b6f4b9bf84a9da27e20c9cbfe887a                                                       |
+        | roles        | Member anotherrole                                                                     |
+        | secret       | ArOy6DYcLeLTRlTmfvF1TH1QmRzYbmD91cbVPOHL3ckyRaLXlaq5pTGJqvCvqg6leEvTI1SQeX3QK-3iwmdPxg |
+        | unrestricted | True                                                                                   |
+        +--------------+----------------------------------------------------------------------------------------+
+
+    and put ``application_credential_id`` and ``application_credential_secret`` in your Dask configuration at ``cloudprovider.openstack.application_credential_id``
+    and ``cloudprovider.openstack.application_credential_secret``. 
+
+All of this variables can be gathered from either `OpenStack RC file <https://docs.openstack.org/newton/user-guide/common/cli-set-environment-variables-using-openstack-rc.html>`_ 
+or `clouds.yaml file <https://docs.openstack.org/python-openstackclient/latest/configuration/index.html>`_.
+
+Example Config File
+^^^^^^^^^^^^^^
+.. code-block:: yaml
+
+   # ~/.config/dask/cloudprovider.yaml
+
+    cloudprovider:
+      openstack:
+        region: "RegionOne"
+        auth_url: "https://cloud.home.karatosun.xyz:5000"
+        application_credential_id: "0a0372dbedfb4e82ab66449c3316ef1e"
+        application_credential_secret: "ArOy6DYcLeLTRlTmfvF1TH1QmRzYbmD91cbVPOHL3ckyRaLXlaq5pTGJqvCvqg6leEvTI1SQeX3QK-3iwmdPxg"
+        auth_type: "v3applicationcredential"
+
+You can also export them as environment variables.
+
+.. code-block:: console
+
+   $ export DASK_CLOUDPROVIDER__APPLICATION_CREDENTIAL_ID="0a0372dbedfb4e82ab66449c3316ef1e"
+
+
+.. autoclass:: OpenStackCluster
+   :members:
diff --git a/examples/OpenstackCluster-scorepredict.ipynb b/examples/OpenstackCluster-scorepredict.ipynb
new file mode 100644
index 00000000..b8d83fb3
--- /dev/null
+++ b/examples/OpenstackCluster-scorepredict.ipynb
@@ -0,0 +1,1270 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "bc03588b-e539-4d6f-8c5c-13b9c5a499e1",
+   "metadata": {},
+   "source": [
+    "# Score and Predict Large Datasets with Dask Openstack Cloud Provider"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "58a2fdac-0f03-48df-bc6b-286515761ba6",
+   "metadata": {},
+   "source": [
+    "This example combines the [Score and Predict Large Datasets example at dask-examples git repository](https://github.com/dask/dask-examples/blob/main/machine-learning/parallel-prediction.ipynb) with Dask Openstack Cloud Provider.\n",
+    "\n",
+    "Details: https://examples.dask.org/machine-learning/parallel-prediction.html"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d7269385-d165-4d33-884d-0cf9b9f1590d",
+   "metadata": {},
+   "source": [
+    "## Prerequisites"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4db66a79-0648-40d3-8c7d-f1b8d69f6c14",
+   "metadata": {},
+   "source": [
+    "```bash\n",
+    "pip install dask-cloudprovider\n",
+    "pip install numpy scikit-learn dask_ml\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "id": "b1973e66-8d3b-4f30-bcac-9e506a1d0ca3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# > (optional) Let's disable the deprecation warnings to improve readability.\n",
+    "import warnings\n",
+    "warnings.filterwarnings('ignore', category=UserWarning)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4000888b-e720-4ea2-955c-9bcbee7a5db3",
+   "metadata": {},
+   "source": [
+    "## Create and Connect to Dask Cluster with Openstack Cloud Provider"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "id": "5b745083-bb26-4fe9-a4f6-f7d049628a79",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import dask\n",
+    "import dask_cloudprovider\n",
+    "from instances import OpenStackCluster\n",
+    "from dask.distributed import Client, progress"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "id": "169db10e-b9cf-484f-9d3d-115272eec85d",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Launching cluster with the following configuration: \n",
+      "  OS Image: ubuntu-22-04 \n",
+      "  Flavor: 4vcpu-8gbram-50gbdisk \n",
+      "  Docker Image: armagankaratosun/dask-ml:latest \n",
+      "  Security Group: all-open \n",
+      "Creating scheduler instance\n",
+      "dask-d523cb04-scheduler\n",
+      "\tInternal IP: 10.0.30.30\n",
+      "\tExternal IP: None\n",
+      "Waiting for scheduler to run at 10.0.30.30:8786\n",
+      "Scheduler is running\n",
+      "Creating worker instance\n",
+      "Creating worker instance\n",
+      "dask-d523cb04-worker-96fd7205\n",
+      "\tInternal IP: 10.0.30.95\n",
+      "\tExternal IP: None\n",
+      "dask-d523cb04-worker-e0f7591e\n",
+      "\tInternal IP: 10.0.30.107\n",
+      "\tExternal IP: None\n"
+     ]
+    }
+   ],
+   "source": [
+    "cluster = OpenStackCluster(n_workers=2, shutdown_on_close=True, docker_image=\"armagankaratosun/dask-ml:latest\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "abdbec11-1154-43d3-91c1-55d03d5935dc",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "client = Client(cluster)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "id": "9c413324-904c-41af-bf10-a82ecf10d2c0",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "    <div style=\"width: 24px; height: 24px; background-color: #e1e1e1; border: 3px solid #9D9D9D; border-radius: 5px; position: absolute;\"> </div>\n",
+       "    <div style=\"margin-left: 48px;\">\n",
+       "        <h3 style=\"margin-bottom: 0px;\">Client</h3>\n",
+       "        <p style=\"color: #9D9D9D; margin-bottom: 0px;\">Client-6f338508-661e-11ef-936f-2a7e43ef1ca5</p>\n",
+       "        <table style=\"width: 100%; text-align: left;\">\n",
+       "\n",
+       "        <tr>\n",
+       "        \n",
+       "            <td style=\"text-align: left;\"><strong>Connection method:</strong> Cluster object</td>\n",
+       "            <td style=\"text-align: left;\"><strong>Cluster type:</strong> instances.OpenStackCluster</td>\n",
+       "        \n",
+       "        </tr>\n",
+       "\n",
+       "        \n",
+       "            <tr>\n",
+       "                <td style=\"text-align: left;\">\n",
+       "                    <strong>Dashboard: </strong> <a href=\"http://10.0.30.30:8787/status\" target=\"_blank\">http://10.0.30.30:8787/status</a>\n",
+       "                </td>\n",
+       "                <td style=\"text-align: left;\"></td>\n",
+       "            </tr>\n",
+       "        \n",
+       "\n",
+       "        </table>\n",
+       "\n",
+       "        \n",
+       "\n",
+       "        \n",
+       "            <details>\n",
+       "            <summary style=\"margin-bottom: 20px;\"><h3 style=\"display: inline;\">Cluster Info</h3></summary>\n",
+       "            <div class=\"jp-RenderedHTMLCommon jp-RenderedHTML jp-mod-trusted jp-OutputArea-output\">\n",
+       "    <div style=\"width: 24px; height: 24px; background-color: #e1e1e1; border: 3px solid #9D9D9D; border-radius: 5px; position: absolute;\">\n",
+       "    </div>\n",
+       "    <div style=\"margin-left: 48px;\">\n",
+       "        <h3 style=\"margin-bottom: 0px; margin-top: 0px;\">OpenStackCluster</h3>\n",
+       "        <p style=\"color: #9D9D9D; margin-bottom: 0px;\">3b3f98df</p>\n",
+       "        <table style=\"width: 100%; text-align: left;\">\n",
+       "            <tr>\n",
+       "                <td style=\"text-align: left;\">\n",
+       "                    <strong>Dashboard:</strong> <a href=\"http://10.0.30.30:8787/status\" target=\"_blank\">http://10.0.30.30:8787/status</a>\n",
+       "                </td>\n",
+       "                <td style=\"text-align: left;\">\n",
+       "                    <strong>Workers:</strong> 2\n",
+       "                </td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                <td style=\"text-align: left;\">\n",
+       "                    <strong>Total threads:</strong> 8\n",
+       "                </td>\n",
+       "                <td style=\"text-align: left;\">\n",
+       "                    <strong>Total memory:</strong> 15.32 GiB\n",
+       "                </td>\n",
+       "            </tr>\n",
+       "            \n",
+       "        </table>\n",
+       "\n",
+       "        <details>\n",
+       "            <summary style=\"margin-bottom: 20px;\">\n",
+       "                <h3 style=\"display: inline;\">Scheduler Info</h3>\n",
+       "            </summary>\n",
+       "\n",
+       "            <div style=\"\">\n",
+       "    <div>\n",
+       "        <div style=\"width: 24px; height: 24px; background-color: #FFF7E5; border: 3px solid #FF6132; border-radius: 5px; position: absolute;\"> </div>\n",
+       "        <div style=\"margin-left: 48px;\">\n",
+       "            <h3 style=\"margin-bottom: 0px;\">Scheduler</h3>\n",
+       "            <p style=\"color: #9D9D9D; margin-bottom: 0px;\">Scheduler-c3c079d0-f8e5-4ce6-8f11-d26e8654fe07</p>\n",
+       "            <table style=\"width: 100%; text-align: left;\">\n",
+       "                <tr>\n",
+       "                    <td style=\"text-align: left;\">\n",
+       "                        <strong>Comm:</strong> tls://10.0.30.30:8786\n",
+       "                    </td>\n",
+       "                    <td style=\"text-align: left;\">\n",
+       "                        <strong>Workers:</strong> 2\n",
+       "                    </td>\n",
+       "                </tr>\n",
+       "                <tr>\n",
+       "                    <td style=\"text-align: left;\">\n",
+       "                        <strong>Dashboard:</strong> <a href=\"http://10.0.30.30:8787/status\" target=\"_blank\">http://10.0.30.30:8787/status</a>\n",
+       "                    </td>\n",
+       "                    <td style=\"text-align: left;\">\n",
+       "                        <strong>Total threads:</strong> 8\n",
+       "                    </td>\n",
+       "                </tr>\n",
+       "                <tr>\n",
+       "                    <td style=\"text-align: left;\">\n",
+       "                        <strong>Started:</strong> 4 minutes ago\n",
+       "                    </td>\n",
+       "                    <td style=\"text-align: left;\">\n",
+       "                        <strong>Total memory:</strong> 15.32 GiB\n",
+       "                    </td>\n",
+       "                </tr>\n",
+       "            </table>\n",
+       "        </div>\n",
+       "    </div>\n",
+       "\n",
+       "    <details style=\"margin-left: 48px;\">\n",
+       "        <summary style=\"margin-bottom: 20px;\">\n",
+       "            <h3 style=\"display: inline;\">Workers</h3>\n",
+       "        </summary>\n",
+       "\n",
+       "        \n",
+       "        <div style=\"margin-bottom: 20px;\">\n",
+       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
+       "            <div style=\"margin-left: 48px;\">\n",
+       "            <details>\n",
+       "                <summary>\n",
+       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: dask-d523cb04-worker-96fd7205</h4>\n",
+       "                </summary>\n",
+       "                <table style=\"width: 100%; text-align: left;\">\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Comm: </strong> tls://10.0.30.95:40477\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Total threads: </strong> 4\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Dashboard: </strong> <a href=\"http://10.0.30.95:43771/status\" target=\"_blank\">http://10.0.30.95:43771/status</a>\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Memory: </strong> 7.66 GiB\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Nanny: </strong> tls://10.0.30.95:44951\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\"></td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
+       "                            <strong>Local directory: </strong> /tmp/dask-scratch-space/worker-e5rljt6_\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                </table>\n",
+       "            </details>\n",
+       "            </div>\n",
+       "        </div>\n",
+       "        \n",
+       "        <div style=\"margin-bottom: 20px;\">\n",
+       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
+       "            <div style=\"margin-left: 48px;\">\n",
+       "            <details>\n",
+       "                <summary>\n",
+       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: dask-d523cb04-worker-e0f7591e</h4>\n",
+       "                </summary>\n",
+       "                <table style=\"width: 100%; text-align: left;\">\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Comm: </strong> tls://10.0.30.107:35117\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Total threads: </strong> 4\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Dashboard: </strong> <a href=\"http://10.0.30.107:46297/status\" target=\"_blank\">http://10.0.30.107:46297/status</a>\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Memory: </strong> 7.66 GiB\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Nanny: </strong> tls://10.0.30.107:43675\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\"></td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
+       "                            <strong>Local directory: </strong> /tmp/dask-scratch-space/worker-5l075jui\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                </table>\n",
+       "            </details>\n",
+       "            </div>\n",
+       "        </div>\n",
+       "        \n",
+       "\n",
+       "    </details>\n",
+       "</div>\n",
+       "\n",
+       "        </details>\n",
+       "    </div>\n",
+       "</div>\n",
+       "            </details>\n",
+       "        \n",
+       "\n",
+       "    </div>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "<Client: 'tls://10.0.30.30:8786' processes=2 threads=8, memory=15.32 GiB>"
+      ]
+     },
+     "execution_count": 55,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "client"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bac247cc-e089-4a2d-9f6b-b5f565cf90d1",
+   "metadata": {},
+   "source": [
+    "## Score and Predict Large Datasets"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "id": "68f0aec9-36af-4818-b9b3-c9af6dcede84",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import dask.array as da\n",
+    "from sklearn.datasets import make_classification"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0dcb00a8-6ba6-40bb-bcbc-e30e47af0ec1",
+   "metadata": {},
+   "source": [
+    "We'll generate a small random dataset with scikit-learn."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "id": "74433cd6-5997-424f-9004-723f6748ad21",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[ 1.53682958, -1.39869399],\n",
+       "       [ 1.36917601, -0.63734411],\n",
+       "       [ 0.50231787, -0.45910529],\n",
+       "       [ 1.83319262, -1.29808229],\n",
+       "       [ 1.04235568,  1.12152929]])"
+      ]
+     },
+     "execution_count": 57,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "X_train, y_train = make_classification(\n",
+    "    n_features=2, n_redundant=0, n_informative=2,\n",
+    "    random_state=1, n_clusters_per_class=1, n_samples=1000)\n",
+    "X_train[:5]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "54d40a88-145d-4fb0-bafd-b6d5f852f5dd",
+   "metadata": {},
+   "source": [
+    "And we'll clone that dataset many times with dask.array. X_large and y_large represent our larger than memory dataset."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "id": "92067947-c8ca-4bd6-a589-9b8c877b96ca",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 1.53 MiB </td>\n",
+       "                        <td> 15.62 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (100000, 2) </td>\n",
+       "                        <td> (1000, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 100 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
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+       "\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "dask.array<concatenate, shape=(100000, 2), dtype=float64, chunksize=(1000, 2), chunktype=numpy.ndarray>"
+      ]
+     },
+     "execution_count": 58,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Scale up: increase N, the number of times we replicate the data.\n",
+    "N = 100\n",
+    "X_large = da.concatenate([da.from_array(X_train, chunks=X_train.shape)\n",
+    "                          for _ in range(N)])\n",
+    "y_large = da.concatenate([da.from_array(y_train, chunks=y_train.shape)\n",
+    "                          for _ in range(N)])\n",
+    "X_large"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ea21bdbb-fbe5-4801-8132-b41d4d62f190",
+   "metadata": {},
+   "source": [
+    "Since our training dataset fits in memory, we can use a scikit-learn estimator as the actual estimator fit during training. But we know that we'll want to predict for a large dataset, so we'll wrap the scikit-learn estimator with ParallelPostFit."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "id": "3df99eb7-c643-4f00-a41c-d3e4f0f37a12",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sklearn.linear_model import LogisticRegressionCV\n",
+    "from dask_ml.wrappers import ParallelPostFit"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "id": "aa0dfd51-ab6b-4709-bd5a-465c1d0f8350",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "clf = ParallelPostFit(LogisticRegressionCV(cv=3), scoring=\"r2\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "86d0c69c-2a06-4f6b-b59f-99301786f9d7",
+   "metadata": {},
+   "source": [
+    "See the note in the dask-ml's documentation about when and why a scoring parameter is needed: https://ml.dask.org/modules/generated/dask_ml.wrappers.ParallelPostFit.html#dask_ml.wrappers.ParallelPostFit.\n",
+    "\n",
+    "Now we'll call clf.fit. Dask-ML does nothing here, so this step can only use datasets that fit in memory."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "id": "7157844d-3d66-41d0-8360-0b4e4a700ff6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style>#sk-container-id-3 {\n",
+       "  /* Definition of color scheme common for light and dark mode */\n",
+       "  --sklearn-color-text: black;\n",
+       "  --sklearn-color-line: gray;\n",
+       "  /* Definition of color scheme for unfitted estimators */\n",
+       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
+       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
+       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
+       "  --sklearn-color-unfitted-level-3: chocolate;\n",
+       "  /* Definition of color scheme for fitted estimators */\n",
+       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
+       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
+       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
+       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
+       "\n",
+       "  /* Specific color for light theme */\n",
+       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
+       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-icon: #696969;\n",
+       "\n",
+       "  @media (prefers-color-scheme: dark) {\n",
+       "    /* Redefinition of color scheme for dark theme */\n",
+       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
+       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-icon: #878787;\n",
+       "  }\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 pre {\n",
+       "  padding: 0;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 input.sk-hidden--visually {\n",
+       "  border: 0;\n",
+       "  clip: rect(1px 1px 1px 1px);\n",
+       "  clip: rect(1px, 1px, 1px, 1px);\n",
+       "  height: 1px;\n",
+       "  margin: -1px;\n",
+       "  overflow: hidden;\n",
+       "  padding: 0;\n",
+       "  position: absolute;\n",
+       "  width: 1px;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-dashed-wrapped {\n",
+       "  border: 1px dashed var(--sklearn-color-line);\n",
+       "  margin: 0 0.4em 0.5em 0.4em;\n",
+       "  box-sizing: border-box;\n",
+       "  padding-bottom: 0.4em;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-container {\n",
+       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+       "     so we also need the `!important` here to be able to override the\n",
+       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+       "  display: inline-block !important;\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-text-repr-fallback {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-parallel-item,\n",
+       "div.sk-serial,\n",
+       "div.sk-item {\n",
+       "  /* draw centered vertical line to link estimators */\n",
+       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+       "  background-size: 2px 100%;\n",
+       "  background-repeat: no-repeat;\n",
+       "  background-position: center center;\n",
+       "}\n",
+       "\n",
+       "/* Parallel-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel-item::after {\n",
+       "  content: \"\";\n",
+       "  width: 100%;\n",
+       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+       "  flex-grow: 1;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel {\n",
+       "  display: flex;\n",
+       "  align-items: stretch;\n",
+       "  justify-content: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel-item {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel-item:first-child::after {\n",
+       "  align-self: flex-end;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel-item:last-child::after {\n",
+       "  align-self: flex-start;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel-item:only-child::after {\n",
+       "  width: 0;\n",
+       "}\n",
+       "\n",
+       "/* Serial-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-serial {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "  align-items: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  padding-right: 1em;\n",
+       "  padding-left: 1em;\n",
+       "}\n",
+       "\n",
+       "\n",
+       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+       "clickable and can be expanded/collapsed.\n",
+       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
+       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+       "*/\n",
+       "\n",
+       "/* Pipeline and ColumnTransformer style (default) */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-toggleable {\n",
+       "  /* Default theme specific background. It is overwritten whether we have a\n",
+       "  specific estimator or a Pipeline/ColumnTransformer */\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable label */\n",
+       "#sk-container-id-3 label.sk-toggleable__label {\n",
+       "  cursor: pointer;\n",
+       "  display: block;\n",
+       "  width: 100%;\n",
+       "  margin-bottom: 0;\n",
+       "  padding: 0.5em;\n",
+       "  box-sizing: border-box;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 label.sk-toggleable__label-arrow:before {\n",
+       "  /* Arrow on the left of the label */\n",
+       "  content: \"▸\";\n",
+       "  float: left;\n",
+       "  margin-right: 0.25em;\n",
+       "  color: var(--sklearn-color-icon);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 label.sk-toggleable__label-arrow:hover:before {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable content - dropdown */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-toggleable__content {\n",
+       "  max-height: 0;\n",
+       "  max-width: 0;\n",
+       "  overflow: hidden;\n",
+       "  text-align: left;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-toggleable__content.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-toggleable__content pre {\n",
+       "  margin: 0.2em;\n",
+       "  border-radius: 0.25em;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-toggleable__content.fitted pre {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+       "  /* Expand drop-down */\n",
+       "  max-height: 200px;\n",
+       "  max-width: 100%;\n",
+       "  overflow: auto;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+       "  content: \"▾\";\n",
+       "}\n",
+       "\n",
+       "/* Pipeline/ColumnTransformer-specific style */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific style */\n",
+       "\n",
+       "/* Colorize estimator box */\n",
+       "#sk-container-id-3 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-label label.sk-toggleable__label,\n",
+       "#sk-container-id-3 div.sk-label label {\n",
+       "  /* The background is the default theme color */\n",
+       "  color: var(--sklearn-color-text-on-default-background);\n",
+       "}\n",
+       "\n",
+       "/* On hover, darken the color of the background */\n",
+       "#sk-container-id-3 div.sk-label:hover label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Label box, darken color on hover, fitted */\n",
+       "#sk-container-id-3 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator label */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-label label {\n",
+       "  font-family: monospace;\n",
+       "  font-weight: bold;\n",
+       "  display: inline-block;\n",
+       "  line-height: 1.2em;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-label-container {\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific */\n",
+       "#sk-container-id-3 div.sk-estimator {\n",
+       "  font-family: monospace;\n",
+       "  border: 1px dotted var(--sklearn-color-border-box);\n",
+       "  border-radius: 0.25em;\n",
+       "  box-sizing: border-box;\n",
+       "  margin-bottom: 0.5em;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-estimator.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "/* on hover */\n",
+       "#sk-container-id-3 div.sk-estimator:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-estimator.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
+       "\n",
+       "/* Common style for \"i\" and \"?\" */\n",
+       "\n",
+       ".sk-estimator-doc-link,\n",
+       "a:link.sk-estimator-doc-link,\n",
+       "a:visited.sk-estimator-doc-link {\n",
+       "  float: right;\n",
+       "  font-size: smaller;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1em;\n",
+       "  height: 1em;\n",
+       "  width: 1em;\n",
+       "  text-decoration: none !important;\n",
+       "  margin-left: 1ex;\n",
+       "  /* unfitted */\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted,\n",
+       "a:link.sk-estimator-doc-link.fitted,\n",
+       "a:visited.sk-estimator-doc-link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "/* Span, style for the box shown on hovering the info icon */\n",
+       ".sk-estimator-doc-link span {\n",
+       "  display: none;\n",
+       "  z-index: 9999;\n",
+       "  position: relative;\n",
+       "  font-weight: normal;\n",
+       "  right: .2ex;\n",
+       "  padding: .5ex;\n",
+       "  margin: .5ex;\n",
+       "  width: min-content;\n",
+       "  min-width: 20ex;\n",
+       "  max-width: 50ex;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  box-shadow: 2pt 2pt 4pt #999;\n",
+       "  /* unfitted */\n",
+       "  background: var(--sklearn-color-unfitted-level-0);\n",
+       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted span {\n",
+       "  /* fitted */\n",
+       "  background: var(--sklearn-color-fitted-level-0);\n",
+       "  border: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link:hover span {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
+       "\n",
+       "#sk-container-id-3 a.estimator_doc_link {\n",
+       "  float: right;\n",
+       "  font-size: 1rem;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1rem;\n",
+       "  height: 1rem;\n",
+       "  width: 1rem;\n",
+       "  text-decoration: none;\n",
+       "  /* unfitted */\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 a.estimator_doc_link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "#sk-container-id-3 a.estimator_doc_link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 a.estimator_doc_link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "</style><div id=\"sk-container-id-3\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>ParallelPostFit(estimator=LogisticRegressionCV(cv=3), scoring=&#x27;r2&#x27;)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-7\" type=\"checkbox\" ><label for=\"sk-estimator-id-7\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;ParallelPostFit<span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>ParallelPostFit(estimator=LogisticRegressionCV(cv=3), scoring=&#x27;r2&#x27;)</pre></div> </div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-8\" type=\"checkbox\" ><label for=\"sk-estimator-id-8\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">estimator: LogisticRegressionCV</label><div class=\"sk-toggleable__content fitted\"><pre>LogisticRegressionCV(cv=3)</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-9\" type=\"checkbox\" ><label for=\"sk-estimator-id-9\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;LogisticRegressionCV<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.linear_model.LogisticRegressionCV.html\">?<span>Documentation for LogisticRegressionCV</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>LogisticRegressionCV(cv=3)</pre></div> </div></div></div></div></div></div></div></div></div>"
+      ],
+      "text/plain": [
+       "ParallelPostFit(estimator=LogisticRegressionCV(cv=3), scoring='r2')"
+      ]
+     },
+     "execution_count": 61,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "clf.fit(X_train, y_train)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "262f1ee3-475e-4542-b662-e33be7302f78",
+   "metadata": {},
+   "source": [
+    "Now that training is done, we'll turn to predicting for the full (larger than memory) dataset."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "id": "fd23ebc8-8355-4a01-8493-b9e1f6ceb42a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 781.25 kiB </td>\n",
+       "                        <td> 7.81 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (100000,) </td>\n",
+       "                        <td> (1000,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 100 chunks in 3 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> int64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"6\" y1=\"0\" x2=\"6\" y2=\"25\" />\n",
+       "  <line x1=\"12\" y1=\"0\" x2=\"12\" y2=\"25\" />\n",
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+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"25\" />\n",
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+       "  <line x1=\"50\" y1=\"0\" x2=\"50\" y2=\"25\" />\n",
+       "  <line x1=\"56\" y1=\"0\" x2=\"56\" y2=\"25\" />\n",
+       "  <line x1=\"62\" y1=\"0\" x2=\"62\" y2=\"25\" />\n",
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+       "  <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"25\" />\n",
+       "  <line x1=\"81\" y1=\"0\" x2=\"81\" y2=\"25\" />\n",
+       "  <line x1=\"87\" y1=\"0\" x2=\"87\" y2=\"25\" />\n",
+       "  <line x1=\"93\" y1=\"0\" x2=\"93\" y2=\"25\" />\n",
+       "  <line x1=\"100\" y1=\"0\" x2=\"100\" y2=\"25\" />\n",
+       "  <line x1=\"106\" y1=\"0\" x2=\"106\" y2=\"25\" />\n",
+       "  <line x1=\"112\" y1=\"0\" x2=\"112\" y2=\"25\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >100000</text>\n",
+       "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "dask.array<_predict, shape=(100000,), dtype=int64, chunksize=(1000,), chunktype=numpy.ndarray>"
+      ]
+     },
+     "execution_count": 62,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "y_pred = clf.predict(X_large)\n",
+    "y_pred"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7e59a188-6de6-43fe-9648-54a4b5596c0d",
+   "metadata": {},
+   "source": [
+    "`y_pred` is a Dask array. Workers can write the predicted values to a shared file system, without ever having to collect the data on a single machine.\n",
+    "\n",
+    "Or we can check the models score on the entire large dataset. The computation will be done in parallel, and no single machine will have to hold all the data."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "276d251a-81aa-4d4a-b155-38a1c02ae115",
+   "metadata": {},
+   "source": [
+    "## Results"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "id": "7782c30a-a237-49a0-840d-ebae6dedc6ab",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from dask.distributed import Client, performance_report\n",
+    "from IPython.display import IFrame"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "id": "8bbd740d-81d4-4b4f-84c7-42cefde782e5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "with performance_report(filename=\"dask-report.html\"):\n",
+    "    # Place your Dask computations here\n",
+    "    # For example, a delayed operation or compute()\n",
+    "    result = clf.score(X_large, y_large)    "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "id": "8f01f103-ec33-48e9-b7ce-fbac32f90e62",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "np.float64(0.596)"
+      ]
+     },
+     "execution_count": 65,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "result"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "id": "932eb174-8587-478a-bb68-ccf951ed6b25",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "        <iframe\n",
+       "            width=\"100%\"\n",
+       "            height=\"500px\"\n",
+       "            src=\"dask-report.html\"\n",
+       "            frameborder=\"0\"\n",
+       "            allowfullscreen\n",
+       "            \n",
+       "        ></iframe>\n",
+       "        "
+      ],
+      "text/plain": [
+       "<IPython.lib.display.IFrame at 0x1496dbd90>"
+      ]
+     },
+     "execution_count": 66,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Display the performance report within the notebook\n",
+    "IFrame(src=\"dask-report.html\", width=\"100%\", height=\"500px\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "251cacbb-f69d-4484-991a-e2671876a66c",
+   "metadata": {},
+   "source": [
+    "## Clean Up"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a4678b96-915c-482d-bbe5-c1b5d250dd46",
+   "metadata": {},
+   "source": [
+    "After the prediction, we can close the client and throw-away the Dask Openstack Cloud Cluster"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 67,
+   "id": "1a861ef5-f98c-4ea2-8883-36eaf03eec2d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "client.close()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 68,
+   "id": "19781f45",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Terminated instance dask-d523cb04-worker-96fd7205\n",
+      "Terminated instance dask-d523cb04-worker-e0f7591e\n",
+      "Terminated instance dask-d523cb04-scheduler\n"
+     ]
+    }
+   ],
+   "source": [
+    "cluster.close()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fab56ddf-700c-46e5-80f2-055a8b01d421",
+   "metadata": {},
+   "source": [
+    "## Credits"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3d409e66-838a-4fe6-948c-7d2fc9935fd9",
+   "metadata": {},
+   "source": [
+    "All credit for [Score and Predict Large Datasets](https://github.com/dask/dask-examples/blob/main/machine-learning/parallel-prediction.ipynb) belongs to their respective developers\n",
+    "\n",
+    "* https://examples.dask.org/machine-learning/parallel-prediction.html\n",
+    "* https://github.com/dask/dask-examples/blob/main/machine-learning/parallel-prediction.ipynb"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.14"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/setup.py b/setup.py
index 64ca18a5..5d3f3b78 100644
--- a/setup.py
+++ b/setup.py
@@ -15,6 +15,7 @@
     "digitalocean": ["python-digitalocean>=1.15.0"],
     "gcp": ["google-api-python-client>=1.12.5", "google-auth>=1.23.0"],
     "hetzner": ["hcloud>=1.10.0"],
+    "openstack": ["openstacksdk>=3.3.0"],
 }
 extras_require["all"] = set(pkg for pkgs in extras_require.values() for pkg in pkgs)