Transportation Hub Pipeline

This project is a proof-of-concept of how to execute a basic machine learning pipeline.

.
├── data/                # Directory where pulled data gets placed.
├── docs/                # Directory where documentation goes.
├── models/              # Directory where generated models get placed.
├── notebooks/           # Directory where prototyping notebooks goes.
├── src/                 # Directory where source code goes.
├── Makefile
├── README.md
└── requirements.txt

Prerequisites

• Linux or WSL
• Python 3
• make

Setup

$make env

Creates a Python virtual environment and installs the necessary dependencies.

$export PIPE_USER="your_username_here"
$export PIPE_PW="your_password_here"

Configures the username and password used when connecting to Snowflake.

Basic Usage

$make all

Pulls down data from Snowflake and creates a simple machine learning model.

$make deploy

Deploys the toy model as a local API, which can take inputs and return predictions.

Advanced Usage

$make data

Pulls down data from Snowflake.

$make model

Generates a model from local data.

$make clean

Removes generated files (i.e., data, models, etc.)