Stage 2: Classic Machine Learning
Master core algorithms and build intelligent decision-making systems
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An introductory textbook on statistical learning developed by Stanford University, available in both R and Python versions. It covers classic machine learning algorithms such as regression, classification, and support vector machines, and includes free online courses and experimental code.
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A classic 12-week, 26-lesson machine learning curriculum for beginners developed by Microsoft, learning machine learning through practical application with cultural data from around the world.
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A classic introductory Machine Learning specialization course by Professor Andrew Ng, covering supervised learning, unsupervised learning, and practical machine learning techniques.
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Description
Complete Chinese notes for Andrew Ng's Stanford Machine Learning course, covering 18 chapters from basic concepts to applications, providing learning materials in various formats.
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An educational project that implements fundamental machine learning models and algorithms from scratch in Python, covering various algorithms from linear regression to deep learning, with a focus on transparently demonstrating the internal workings of the algorithms.