Welcome to a hands-on journey into the fascinating world of Machine Learning! This repository contains all the materials for an interactive workshop designed for beginners. Where we look into the core concepts, explore the math behind the models, and build an ML model.
This workshop provides a comprehensive yet approachable introduction to ML. We are focused on hands-on learning, ensuring you write code and see concepts in action. By the end, you will have a solid foundational understanding of:
- The three primary paradigms of machine learning.
- How to perform essential data analysis and visualization.
- The intuition and mathematics behind predictive modeling (Regression).
- The building blocks of deep learning through a practical image classification project.
- Fundamentals of Machine Learning:
- Supervised Learning
- Unsupervised Learning
- Reinforcement Learning
- Hands-On Data Analysis:
- Numerical operations with NumPy
- Data manipulation and analysis with Pandas
- Creating insightful visualizations with Matplotlib
- Linear Regression:
- Understanding the core math: Cost Functions and Gradient Descent.
- Neural Networks & The MNIST Challenge:
- The mathematics behind a simple neural network.
- A complete hands-on session to classify handwritten digits from the famous MNIST dataset.