BOOKS - Deep Learning: A Practical Introduction
US $7.81
330138
330138
Deep Learning: A Practical Introduction
Author: Manel Martinez-Ramon
Year: July 8, 2024
Format: PDF
File size: PDF 16 MB
Language: English
Year: July 8, 2024
Format: PDF
File size: PDF 16 MB
Language: English
An engaging and accessible introduction to deep learning perfect for students and professionalsIn Deep A Practical Introduction, a team of distinguished researchers delivers a book complete with coverage of the theoretical and practical elements of deep learning. The book includes extensive examples, end-of-chapter exercises, homework, exam material, and a GitHub repository containing code and data for all provided examples.Combining contemporary deep learning theory with state-of-the-art tools, the chapters are structured to maximize accessibility for both beginning and intermediate students. The authors have included coverage of TensorFlow, Keras, and Pytorch. Readers will also Thorough introductions to deep learning and deep learning toolsComprehensive explorations of convolutional neural networks, including discussions of their elements, operation, training, and architecturesPractical discussions of recurrent neural networks and non-supervised approaches to deep learningFulsome treatments of generative adversarial networks as well as deep Bayesian neural networks Perfect for undergraduate and graduate students studying computer vision, computer science, artificial intelligence, and neural networks, Deep A Practical Introduction will also benefit practitioners and researchers in the fields of deep learning and machine learning in general.
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