discover · compare · collections · requirements · contribute · feed · watching · stats · help with your tokens
HenryNdubuaku/maths-cs-ai-compendium
Become a cracked AI/ML researcher/engineer with this unconventional textbook covering maths, computing, and ML with intuition.
History and source changes · Reports and owner responses · Compare
Similar
- instillai/machine-learning-course
:speech_balloon: Machine Learning Course with Python:
Why this match
topics algorithms, artificial-intelligence, machine-learning; language differs: TypeScript → Python
- pliang279/awesome-multimodal-ml
Reading list for research topics in multimodal machine learning
Why this match
topics computer-vision, deep-learning, machine-learning; license differs: Apache-2.0 → MIT
- fastai/numerical-linear-algebra
Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course
Why this match
topics algorithms, deep-learning, linear-algebra; language differs: TypeScript → Jupyter Notebook
- ZuzooVn/machine-learning-for-software-engineers
A complete daily plan for studying to become a machine learning engineer.
Why this match
topics artificial-intelligence, deep-learning, machine-learning; license differs: Apache-2.0 → CC-BY-SA-4.0
- NLP-LOVE/ML-NLP
此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现，也是作为一个算法工程师必会的理论基础知识。
Why this match
topics deep-learning, machine-learning, nlp; language differs: TypeScript → Jupyter Notebook
- rushter/MLAlgorithms
Minimal and clean examples of machine learning algorithms implementations
Why this match
topics deep-learning, machine-learning, machine-learning-algorithms; language differs: TypeScript → Python; license differs: Apache-2.0 → MIT
- SerpentAI/SerpentAI
Game Agent Framework. Helping you create AIs / Bots that learn to play any game you own!
Why this match
topics artificial-intelligence, computer-vision, deep-learning; language differs: TypeScript → Python; license differs: Apache-2.0 → MIT
- ahmedbahaaeldin/From-0-to-Research-Scientist-resources-guide
Detailed and tailored guide for undergraduate students or anybody want to dig deep into the field of AI with solid foundation.
Why this match
topics deep-learning, linear-algebra, machine-learning