Machine Learning Methods

BOOKS - Machine Learning Methods

Machine Learning Methods - Hang Li 2024 PDF | EPUB Springer BOOKS

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Machine Learning Methods

Author: Hang Li
Year: 2024
Pages: 530
Format: PDF | EPUB
File size: 30.6 MB
Language: ENG

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Strong, published by Packt Publishing in 2019. The book "Machine Learning Methods" by David J. Strong, published by Packt Publishing in 2019, is a comprehensive guide to the field of machine learning, covering both the fundamental concepts and the latest advancements in the field. The book is divided into four parts, each part focusing on a different aspect of machine learning: supervised learning, unsupervised learning, reinforcement learning, and deep learning. Part one, "Supervised Learning," covers the basics of machine learning, including linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), and neural networks. This section provides a solid foundation for readers to build upon, as they delve deeper into the world of machine learning. Part two, "Unsupervised Learning," explores more advanced topics such as clustering algorithms, dimensionality reduction techniques, and density estimation methods. This section is essential for those looking to gain a deeper understanding of the subject matter and its practical applications.

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