This repository contains code and notes related to various machine learning concepts that I am studying for my GATE exam preparation.
- Introduction to Machine Learning
- Linear Regression for 1 dimension data ( 1 independant and 1 dependant variable each )
- Linear Regression for 2 dimension data ( 2 independant and 1 dependant variable each, 3d plot )
- Learning pandas for machine learning
Each concept is explained in a Jupyter Notebook with code examples and explanations. You can navigate through the notebooks to learn and practice the concepts.
- GATE Exam Official Website
- Machine Learning by Andrew Ng (Coursera)
- Introduction to Machine Learning with Python by Andreas C. Müller and Sarah Guido
Feel free to fork this repository and contribute by adding more concepts, improving explanations, or fixing any issues.