Includes my personal modification and annotations of the Machine Learning Specialisation from Stanford University and Deeplearning.ai on Coursera (2022), instructed by Prof. Andrew Ng.
This repository is dedicated to content inspired by the Machine Learning Specialisation by Prof. Andrew Ng from Stanford University, presented on Coursera.
Please note: The content here is primarily for educational and reference purposes. While I have modified and adapted some of the code for specific use cases or clarity, the foundational model designs and core theory remain consistent with Prof. Andrew Ng's teachings. All original ideas, material, and course content are fully credited to Prof. Andrew Ng and the course creators. I advocate enrolling in the original course to gain a holistic understanding and benefit from hands-on experience.
This repository is organized into three primary parts, reflecting the structure of the specialisation:
- Course 1: Supervised Machine Learning: Regression and Classification
- Course 2: Advanced Learning Algorithms
- Course 3: Unsupervised Learning, Recommenders, Reinforcement Learning
You'll discover summaries, notes, and insights pertaining to each course within. For comprehensive content and well-organized modules, kindly navigate to the respective folders in this repository.