Tsinghua University Press

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Description

This book introduces the theory, model and algorithm implementation of machine learning, including the construction of machine learning experiment environment, data cleaning, model evaluation, classification and regression of supervised learning, clustering and dimensionality reduction of unsupervised learning and other underlying algorithms. This book covers K-nearest neighbor algorithms, decision trees, supporting vector machines, BP neural networks, convolutional neural networks, recurrent neural networks, ensemble learning, K means clustering, fuzzy clustering, principal and independent component analysis, etc.

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