Full-Stack Machine Learning

Intro

This repository contains the supplementary material for the Full Stack Machine Learning Course (e.g. Digethic Data Scientist / AI-Engineer).

All notebooks under /notepads are structured and can be identified via the folder number and notebook code. All notebooks correspond to the slides and videos produces for this course.

E.g. this identifier referes to folder 2 and notebook with code EDA.

Setup

Linux and Mac Users

• run the setup script ./setup.sh or sh setup.sh

Windows Users

• run the setup script .\setup.ps1
• if running the script does not work due to access rights, try following command in your terminal: Set-ExecutionPolicy -ExecutionPolicy RemoteSigned -Scope CurrentUser

Development

• Mac/Linux: activate python environment: source .venv/bin/activate
• Windows: activate python environment: .\.venv\Scripts\Activate.ps1
• run python script: python <filename.py> , e.g. python train.py
• install new dependency: pip install sklearn
• save current installed dependencies back to requirements.txt: pip freeze > requirements.txt
• to start Jupyter lab run jupyter lab --ip=127.0.0.1 --port=8888