Skip to content

uclaacmai/advanced-track-fall18

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

30 Commits
 
 
 
 
 
 
 
 

Repository files navigation

ACM AI Advanced Workshop Series

Code, Slides, & Materials for our Advanced Workshop Series, Fall Quarter 2018

Link to Slides Used

Workshop 1: https://tinyurl.com/aiadvancedf181

Workshop 2: https://tinyurl.com/aiadvancedf182

Workshop 3: https://tinyurl.com/aiadvancedf183

Setup Instructions

Getting a Python and Machine Learning Environment Up and Running

Please complete these tasks before the workshop in order to hit the ground running! Don’t worry if you run into some errors though, we will have mentors on hand to help you through setup.

Mac & Linux Installation Instructions

If you don't have brew, install it by using the command available here.

(Optional: We recommend a python3 installation. Your mac currently likely comes with Python 2 as the default built-in.)

If you don't have python3 installed (check by typing python3 in the terminal), run brew install python3. This will install python3 and a package manager, pip3 for you. This may take a while.

Ubuntu/Debian Specific: Installing Python3 To get Python 3 (we recommend using this over Python 2), run sudo apt-get update, then sudo apt-get install python3.6

Run pip3 install numpy matplotlib tensorflow sklearn jupyter scipy if you are running Python3, otherwise run pip install numpy matplotlib tensorflow jupyter sklearn scipy. This command may have to be prefaced with the sudo keyword.

If you have installed any of these packages before, make sure to run pip install [PACKAGE] --upgrade to ensure that you have the latest version.

Execute the following Python program:

import numpy as np
import matplotlib.pyplot as plt
import tensorflow as tf
import sklearn
hello = tf.constant('Hello, Tensorflow!')
sess = tf.Session()
print(sess.run(hello))

If it runs without any errors, then you're good to go!

Windows Installation Instructions

Highly recommended: Installing with the Anaconda Distribution

  • Anaconda is a package managing tool for Python that can be installed for both Mac and Windows. We've found that going with Anaconda results in the least installation issues for those of you who are using Windows.

First, download Anaconda at this link: https://www.anaconda.com/download/#windows. We recommend downloading the Python 3.6 installation.

After Anaconda has downloaded, open it up and install it. The installation process takes a while, but after you should see a screen with the option "Register Anaconda as my default Python". Check this, and continue.

Once the installation is finished, you should be able to open up the Anaconda prompt, and invoke python. In the python interpreter, the commands import sklearn import matplotlib import numpy should all work.

Finally, install Tensorflow with the Anaconda package manager, known as conda: conda install Tensorflow. Now, you should be able to execute the following program without any issues:

import numpy as np
import matplotlib.pyplot as plt
import tensorflow as tf
hello = tf.constant('Hello, Tensorflow!')
sess = tf.Session()
print(sess.run(hello))

For additional details on Anaconda installation, see this helpful link.

Installing on Windows without Anaconda

If you don't want to use Anaconda, follow these steps to get your environment and tools up and running.

Source to refer: https://www.tensorflow.org/install/install_windows

Install Python 3.5 if it's not currently installed on your computer: https://www.python.org/downloads/release/python-352/

TensorFlow only supports version 3.5.x of Python on Windows. Note that Python 3.5.x comes with the pip3 package manager, which is the program you'll use to install TensorFlow. Note that this means you cannot use Python 2 if you have it installed.

To install tensorflow, issue the following command: C:\> pip3 install --upgrade tensorflow

Also issue the following commands for jupyter, sklearn, and matplotlib.

C:\> pip3 install --upgrade jupyter

C:\> pip3 install --upgrade matplotlib

C:\> pip3 install --upgrade sklearn

Next, invoke Python through the terminal:

C:> python

In the terminal, execute the following python program:

import numpy as np
import matplotlib.pyplot as plt
import tensorflow as tf
hello = tf.constant('Hello, Tensorflow!')
sess = tf.Session()
print(sess.run(hello))

If it runs without errors, you're good to go!

About

ACM AI's Advanced Track Workshops, Fall 2018

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published