deep learning / machine learning education and interview prep
A comprehensive Chinese-language Q&A book covering math, machine learning, deep learning, and computer vision concepts for AI interview preparation.
Same problem, same approach. Swapping one for another is a config change, not a rewrite.
Choose for a similar AI interview-prep collection with code examples and a focus on NLP; actively maintained and Chinese-language.
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。
Solves the same problem with a different architecture or at a different layer. Expect to rewrite the integration.
Choose for a code-first, challenge-based introduction to ML rather than a Q&A review; it is lighter on theory.
100 Days of ML Coding
Choose for a modern, practical deep learning book with code-first lessons and a strong focus on applications; more up-to-date than the seed's 2018 content.
The fastai book, published as Jupyter Notebooks
Choose for interactive, math-explained Python implementations of classic ML algorithms; more hands-on and less exam-oriented.
🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained
Choose for a complete, structured PyTorch-based deep learning textbook; more pedagogical and code-first than the seed's Q&A style.
本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。
Choose for a broad, Chinese-language tutorial collection covering data analysis, ML, and DL; more code and example-driven than the seed.
AiLearning：数据分析+机器学习实战+线性代数+PyTorch+NLTK+TF2
Choose for Chinese-language video-guided ML algorithm implementations; more hands-on and narrower than the seed.
A repository contains more than 12 common statistical machine learning algorithm implementations. 常见10余种机器学习算法原理与实现及视频讲解。@跟我学机器学习 出品
Choose for simple Python examples of common ML algorithms; more code and less comprehensive theory.
Python code for common Machine Learning Algorithms
These projects were analysed and named DeepLearning-500-questions among their alternatives. The relationship is not symmetric — how DeepLearning-500-questions rates them is a separate judgement, made when DeepLearning-500-questions is analysed in its own right.
calls DeepLearning-500-questions “Choose this when you want a Chinese Q&A compendium covering ML/DL theory for interview prep.”
吴恩达老师的机器学习课程个人笔记
calls DeepLearning-500-questions “choose for Chinese-language ML/DL interview Q&A instead of code drills.”
100-Days-Of-ML-Code中文版