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Deep learning with R /

Chollet, François.

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Deep learning with R /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Deep learning with R // François Chollet with Tomasz Kalinowski and J.J. Allaire.
Author:	Chollet, François.
other author:	Kalinowski, Tomasz.
Published:	Shelter Island, NY :Manning, : c2022.,
Description:	xviii, 548 p. :ill. ;24 cm.
Notes:	Includes index.
[NT 15003449]:	What is deep learning? -- The mathematical building blocks of neural networks -- Introduction to Keras and TensorFlow -- Getting started with neural networks : classification and regression -- Fundamentals of machine learning -- The universal workflow of machine learning -- Working with Keras : a deep dive -- Introduction to deep learning for computer vision -- Advanced deep learning for computer vision -- Deep learning for time series -- Deep learning for text -- Generative deep learning -- Best practices for the real world -- Conclusions.
Subject:	Machine learning. -
ISBN:	9781633439849

Deep learning with R /
Chollet, François.

Deep learning with R /François Chollet with Tomasz Kalinowski and J.J. Allaire. - 2nd ed. - Shelter Island, NY :Manning,c2022. - xviii, 548 p. :ill. ;24 cm.

Includes index.

What is deep learning? -- The mathematical building blocks of neural networks -- Introduction to Keras and TensorFlow -- Getting started with neural networks : classification and regression -- Fundamentals of machine learning -- The universal workflow of machine learning -- Working with Keras : a deep dive -- Introduction to deep learning for computer vision -- Advanced deep learning for computer vision -- Deep learning for time series -- Deep learning for text -- Generative deep learning -- Best practices for the real world -- Conclusions.

Deep learning has become essential knowledge for data scientists, researchers, and software developers. The R language APIs for Keras and TensorFlow put deep learning within reach for all R users, even if they have no experience with advanced machine learning or neural networks. This book shows you how to get started on core DL tasks like computer vision, natural language processing, and more using R. "Deep learning with R, second edition" is a hands-on guide to deep learning using the R language. As you move through this book, you'll quickly lock in the foundational ideas of deep learning. The intuitive explanations, crisp illustrations, and clear examples guide you through core DL skills like image processing and text manipulation, and even advanced features like transformers. This revised and expanded new edition is adapted from "Deep learning with Python, second edition" by François Chollet, the creator of the Keras library.

ISBN: 9781633439849US29.99Subjects--Topical Terms:

533906
Machine learning.

LC Class. No.: QA276.45.R3 / C46 2022

Dewey Class. No.: 006.31

Deep learning with R /
LDR:02117cam a2200205 a 4500 001 2288453
008 220915s2022 nyua 001 0 eng d
020 $a 9781633439849 $q (pbk.) : $c US29.99
020 $a 1633439844 $q (pbk.)
035 $a (OCoLC)1343210227
040 $a EUN $b eng $c EUN $d OCLCQ $d JRZ
050 # 4 $a QA276.45.R3 $b C46 2022
082 0 4 $a 006.31 $2 23
100 1 $a Chollet, François. $3 3578652
245 1 0 $a Deep learning with R / $c François Chollet with Tomasz Kalinowski and J.J. Allaire.
250 $a 2nd ed.
260 # $a Shelter Island, NY : $b Manning, $c c2022.
300 $a xviii, 548 p. : $b ill. ; $c 24 cm.
500 $a Includes index.
500 $a Previous edition: 2018.
505 0 # $a What is deep learning? -- The mathematical building blocks of neural networks -- Introduction to Keras and TensorFlow -- Getting started with neural networks : classification and regression -- Fundamentals of machine learning -- The universal workflow of machine learning -- Working with Keras : a deep dive -- Introduction to deep learning for computer vision -- Advanced deep learning for computer vision -- Deep learning for time series -- Deep learning for text -- Generative deep learning -- Best practices for the real world -- Conclusions.
520 # $a Deep learning has become essential knowledge for data scientists, researchers, and software developers. The R language APIs for Keras and TensorFlow put deep learning within reach for all R users, even if they have no experience with advanced machine learning or neural networks. This book shows you how to get started on core DL tasks like computer vision, natural language processing, and more using R. "Deep learning with R, second edition" is a hands-on guide to deep learning using the R language. As you move through this book, you'll quickly lock in the foundational ideas of deep learning. The intuitive explanations, crisp illustrations, and clear examples guide you through core DL skills like image processing and text manipulation, and even advanced features like transformers. This revised and expanded new edition is adapted from "Deep learning with Python, second edition" by François Chollet, the creator of the Keras library.
650 # 0 $a Machine learning. $3 533906
650 # 0 $a R (Computer program language) $3 784593
650 # 0 $a Artificial intelligence. $3 516317
650 # 0 $a Neural networks (Computer science) $3 532070
650 # 0 $a Machine learning $x Technological innovations. $3 3231360
650 # 0 $a Mathematical statistics $x Data processing. $3 532521
650 # 0 $a Computer vision. $3 540671
650 # 0 $a Programming languages (Electronic computers) $3 606806
700 1 # $a Kalinowski, Tomasz. $3 3578653
700 1 # $a Allaire, J. J., $d 1969- $3 3578654