Why?
So I recently started a Data Science course and learnt to use Amazon SageMaker Studio Lab (ASL) to create and run our DS projects. ASL is a free Machine Learning (ML) development environment that provides a web based virtual interface to perform all Data Science and Machine Learning steps. Its really easy to setup and use but I found one drawback for my use case. I wanted a Web Interface for my Data Science apps. So I wanted to test them locally and then deploy it to Heroku. Unfortunately ASL doesn't support browser in its virtual environment. So decided to set it up locally :)
What?
In this blog I'll walk you thru the steps to setup dev environment for Data Science and Machine Learning locally. This is ideal for learning and quickly proto-typing ideas and applications, but not for training production Data Models as it might require a lot of processing power. We are going to use Docker and Visual Studio Code so setup the environment. We will also setup few VS Code plugins during the setup.
How?
Step 1:
Install Docker by following the steps for respective platform here
Step 2:
Install Visual Studio Code by following the steps for respective platform here
Step 3:
In your workspace create a directory called Data Science. This will be the root directory for all Data Science related projects and applications.