DrWaleedAYousef/TeachingGitHub
Pick this if you prefer Mathematica-based GPL teaching materials over Python/Jupyter notebooks.
Teaching Materials for Dr. Waleed A. Yousef
- 1.0k
- Mathematica
- GPL-3.0
dormant2.3y ago
jonkrohn/ML-foundations Alternatives
ML foundations education
Educational curriculum with Jupyter notebooks covering linear algebra, calculus, probability, statistics, algorithms, and optimization for machine learning.
Same job, different approach
Solves the same problem with a different architecture or at a different layer. Expect to rewrite the integration.
HenryNdubuaku/maths-cs-ai-compendiumGitHub
Choose when you want a current TypeScript interactive textbook on maths, computing, and ML instead of Python notebooks.
Become a cracked AI/ML researcher/engineer with this unconventional textbook covering maths, computing, and ML with intuition.
- 7.4k
- TypeScript
- Apache-2.0
active3mo ago
Older generation, or narrower
An earlier or more limited way to do the job. Still the right call when you need something small, proven, or CPU-only.
amitkaps/hackermathGitHub
Use if you want an older MIT-licensed notebook intro to statistics and math for data science, accepting years without updates.
Introduction to Statistics and Basics of Mathematics for Data Science - The Hacker's Way
- 1.4k
- Jupyter Notebook
- MIT
dormant8.9y ago
hrnbot/Basic-Mathematics-for-Machine-LearningGitHub
Choose for Apache-2.0 Jupyter notebooks on basic math for ML when stale dependencies are acceptable.
The motive behind Creating this repo is to feel the fear of mathematics and do what ever you want to do in Machine Learning , Deep Learning and other fields of AI
- 752
- Jupyter Notebook
- Apache-2.0
dormant4.1y ago
Ryota-Kawamura/Mathematics-for-Machine-Learning-and-Data-Science-SpecializationGitHub
Use if you are following the deeplearning.ai specialisation and want its notebook solutions/notes, not a standalone curriculum.
Master the Toolkit of AI and Machine Learning. Mathematics for Machine Learning and Data Science is a beginner-friendly Specialization where you’ll learn the fundamental mathematics toolkit of machine learning: calculus, linear algebra, statistics, and probability.
- 881
- Jupyter Notebook
- none
dormant3.3y ago
fastai/numerical-linear-algebraGitHub
Choose if you only need computational linear algebra and want fast.ai's notebook textbook, not the full ML foundations scope.
Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course
- 11.0k
- Jupyter Notebook
- none
dormant2.5y ago
greyhatguy007/Mathematics-for-Machine-Learning-and-Data-Science-Specialization-CourseraGitHub
Use if you want Coursera specialisation notes/solutions for ML math instead of a self-contained curriculum.
Mathematics for Machine Learning and Data Science Specialization - Coursera - deeplearning.ai - solutions and notes
- 983
- Jupyter Notebook
- none
dormant3.4y ago
Listed as an alternative to
These projects were analysed and named ML-foundations among their alternatives. The relationship is not symmetric — how ML-foundations rates them is a separate judgement, made when ML-foundations is analysed in its own right.
HenryNdubuaku/maths-cs-ai-compendiumGitHub
calls ML-foundations “Use it when you only need ML math prerequisites like linear algebra, calculus, and statistics, not full AI coverage.”
Become a cracked AI/ML researcher/engineer with this unconventional textbook covering maths, computing, and ML with intuition.
7.4kTypeScriptactive