Welcome to the Introduction to Machine Learning (TEDA 1036) repository! This repository contains the readings you need for the course. These notebooks contain the solutions to the student assignments as well.
The primary goal of TEDA 1036 is to provide a practical introduction to machine learning for students with minimal background in mathematics and statistics. The course emphasizes hands-on experience and intuitive understanding over theoretical derivations.
All notebooks in this repository were written and executed using Google Colab, making it easy for students to run the code without requiring the installation of an IDE.
- Python Notebooks: Step-by-step tutorials and exercises to guide you through key machine learning concepts and techniques.
- Datasets: All datasets required for the course are included in the repository for easy access.
Sources and further readings for specific concepts are included at the end each notebook.
This course is based off of Introduction to Machine Learning by Muller and Guido.