aespresso/a_journey_into_math_of_ml resource

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1717 stars · 693 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A collection of Chinese-language machine learning tutorials in Jupyter Notebook form, accompanied by video lectures on YouTube and Bilibili. It covers mathematical foundations like maximum likelihood, logistic regression, and AdaBoost, plus Chinese NLP topics including Transformers, BERT, and HMM-based named entity recognition.

Use cases

• learn the math behind machine learning from scratch
• understand the transformer architecture with visual explanations
• study BERT and language model pretraining in Chinese
• learn hidden Markov models for named entity recognition
• understand the Viterbi algorithm for sequence labeling
• visualize maximum likelihood estimation in 3D
• learn logistic regression with cross-entropy and gradient descent

When to choose

• you prefer Chinese-language explanations of ML and NLP concepts
• you want math-first derivations paired with runnable notebooks and videos
• you are studying classical NLP models like HMM and transformer from the ground up

When to avoid

• you need production-ready ML code or maintained libraries
• you require English-language tutorials
• you need up-to-date coverage of modern LLM techniques

Facets

learning-resource · maturity maintenance

machine-learning nlp data-visualization machine-learning tutorials education python jupyter-notebooks chinese-language video-tutorials transformer bert hmm logistic-regression adaboost maximum-likelihood natural-language-processing

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