This repository is dedicated to the exploration and understanding of Machine Learning, divided into two primary sections: Supervised Machine Learning and Unsupervised Machine Learning. Each section contains a set of exercises, projects, and instructor materials designed to enhance learning and practical application of machine learning concepts.
In this section, we delve into the fundamentals and advanced topics of Supervised Machine Learning, exploring various algorithms and their applications. It is structured as follows:
- 00-Lectures: The notebooks for the course part.
- 01-Exercises: Practical exercises to apply supervised learning concepts.
- 02-Project: A comprehensive project that applies supervised learning techniques to solve a real-world problem.
- 03-Instructors: Materials and notes for instructors to facilitate teaching and understanding of complex concepts.
This section focuses on Unsupervised Machine Learning, exploring how to uncover hidden patterns and correlations in data without predefined labels. It includes:
- 00-Lectures: The notebooks for the course part.
- 01-Exercises: Exercises designed to provide hands-on experience with unsupervised learning algorithms.
- 02-Project: A project section where unsupervised learning methods are applied to unearth insights from datasets.
- 03-Instructors: Instructor resources including lecture notes and guidance for explain