Название: Machine Learning: Theory and PracticeАвтор: Jugal Kalita
Издательство: CRC Press
Год: 2023
Страниц: 299
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB
Machine Learning: Theory and Practice provides an introduction to the most popular methods in Machine Learning (ML). The book covers regression including regularization, tree-based methods including Random Forests and Boosted Trees, Artificial Neural Networks including Convolutional Neural Networks (CNNs), reinforcement learning, and unsupervised learning focused on clustering. Topics are introduced in a conceptual manner along with necessary mathematical details. The explanations are lucid, illustrated with figures and examples. For each machine learning method discussed, the book presents appropriate libraries in the R programming language along with programming examples. These days, the predominant programming languages used in academia as well as industry, are Python and R. R is a statistical package, with an associated language that has powerful libraries for all kinds of machine learning tasks. We will also discuss specific libraries like TensorFlow and Keras in the context of deep learning. We include examples in R in the current edition of the book.
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