MLEveryday/100-Days-Of-ML-Code

Structured curriculum progressing from classical supervised learning algorithms (linear/logistic regression, SVM, decision trees, random forests) through unsupervised clustering to deep learning fundamentals, paired with mathematical foundations in linear algebra and calculus. Includes implementation code using scikit-learn, TensorFlow, and Keras alongside infographics and curated video resources from channels like 3Blue1Brown. Targets Chinese-speaking learners with translated documentation, notebooks, and references to bilibili mirrors of educational content.

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