Welcome to my Machine Learning (ML) Learning Journey repository! This space is a curated collection of all the resources, projects, and insights I have gathered while exploring the exciting field of ML.
Contains hands-on coding exercises focused on specific ML topics. Currently includes:
- Linear Regression
Includes animations created using the MANIM library to visually represent complex mathematical and ML concepts.
This section houses mathematical derivations and Python implementations of core ML algorithms. Highlights include:
alg.py: Gradient Descent, Cost Function, and other fundamental algorithms.
Blog-style writeups explaining ML concepts, including derivations and theoretical foundations.
A sample ML project aimed at predicting premiums using real-world datasets. Includes:
- Preprocessed datasets
- Step-by-step implementation
- Visual and intuitive explanations
- Comprehensive exercises
- Hands-on projects for practical learning
- Python implementations for mathematical algorithms
- Clone the repository:
git clone https://github.com/sumit-sah314/My-ML-Learning-Journey.git