First-Principles-ML
♥Cherished
A structured learning resource that implements fundamental machine learning algorithms from scratch using NumPy, covering everything from mathematical foundations through deep learning and system design. Built for students and interview candidates who need to understand the mechanics behind algorithms rather than just call library functions.
Clauded With Love Rating
7.5 / 10
First-Principles-ML is a comprehensive educational repository implementing fundamental machine learning algorithms from scratch using NumPy, designed for deep understanding and interview preparation. The project covers mathematical foundations, classical ML algorithms, deep learning components, and transformer architectures with a focus on implementation details rather than library usage.
Code Quality6.5
Usefulness8.5
Claude Usage7.0
Documentation8.0
Originality7.5
Highlights
- ✓Excellent pedagogical structure progressing from mathematical foundations through modern architectures like transformers
- ✓Strong philosophy of 'implement don't import' with clear interview-focused approach
- ✓Comprehensive coverage spanning classical ML, deep learning, and modern LLM components with consistent NumPy-first approach
To Improve
- →Add actual code examples and implementation quality assessment since only README is visible
- →Include test coverage and error handling examples to demonstrate production-ready practices