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Editorial Reviews
Product Description
This exciting addition to the McGraw-Hill Series in Computer Science focuses on the concepts and techniques that contribute to the rapidly changing field of machine learning--including probability and statistics, artificial intelligence, and neural networks--unifying them all in a logical and coherent manner. Machine Learning serves as a useful reference tool for software developers and researchers, as well as an outstanding text for college students.
Book Info
Presents the key algorithms and theory that form the core of machine learning. Discusses such theoretical issues as How does learning performance vary with the number of training examples presented? and Which learning algorithms are most appropriate for various types of learning tasks? DLC: Computer algorithms.
This exciting addition to the McGraw-Hill Series in Computer Science focuses on the concepts and techniques that contribute to the rapidly changing field of machine learning--including probability and statistics, artificial intelligence, and neural networks--unifying them all in a logical and coherent manner. Machine Learning serves as a useful reference tool for software developers and researchers, as well as an outstanding text for college students.
Book Info
Presents the key algorithms and theory that form the core of machine learning. Discusses such theoretical issues as How does learning performance vary with the number of training examples presented? and Which learning algorithms are most appropriate for various types of learning tasks? DLC: Computer algorithms.
Product Details
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