machine-learning-fundamentals-from-scratch azaynul10 · COMPLETED
A comprehensive, hand-coded survival guide to Artificial Intelligence and Machine Learning fundamentals. Features step-by-step mathematical derivations, algorithmic implementations from scratch (A* Search, Genetic Algorithms, Minimax, Naive Bayes, Gradient Descent), and structured academic resource roadmaps for developers and students.
github.com/azaynul10/machine-learning-fundamentals-from-scratch · ★ 0 · Forks 0 · Size 1.4 MB
SUMMARY
Technologies 4
Scored 4
Observed 4
Practices 6
Evidence 4
Skips 0
COVERAGE
Analyzed 12 files · 7 commits · 0 API calls
TECHNOLOGIES & DEPTH
Markdown LANGUAGE Depth 70
2 files · PRODUCTION
Python LANGUAGE Depth 70
3 files · PRODUCTION
NumPy LIBRARY Depth 58
2 files · PRODUCTION
pandas LIBRARY Depth 58
2 files · PRODUCTION
PRACTICES
documentation · observedautomated_tests · absentcontinuous_integration · absentcontainerization · absentlinting · absentformatting · absent
ACTIVITY & OWNERSHIP
First commit 2026-06-04
Last commit 2026-06-05
Active months 1
Commits 7