Deep Learning

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Part I of the book offers a rigorous overview of machine learning principles, algorithms, and implementation skills relevant to holistically modeling and manipulating tabular data. Part II studies five dominant deep learning model designs – Artificial Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Attention and Transformers, and Tree-Rooted Networks – through both their ‘default’ usage and their application to tabular data. Part III compounds the power of the previously covered methods by surveying strategies and techniques to supercharge deep learning systems: autoencoders, deep data generation, meta-optimization, multi-model arrangement, and neural network interpretability. Each chapter comes with extensive visualization, code, and relevant research coverage.
AuthorANDRE YE BindingPaperback
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By Max Pumperla, Kevin Ferguson
$5499 $4399
Max Pumperla  is a Data Scientist and Engineer specializing in Deep Learning at the artificial intelligence company He is the co-founder of the Deep Learning platform Kevin Ferguson  has 18 years of experience in distributed systems and data science. He is a data scientist at Honor, and has experience at companies such as Google and Meebo.
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By Tommaso Teofili
$5999 $4799
Tommaso Teofili  is a software engineer with a passion for open source and machine learning. As a member of the Apache Software Foundation, he contributes to a number of open source projects, ranging from topics like information retrieval (such as Lucene and Solr) to natural language processing and machine translation (including OpenNLP, Joshua, and UIMA).
AuthorTommaso Teofili BindingPaperback
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By Shanqing Cai
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Shanqing Cai  is one of the developers of TensorFlow, a popular open-source framework for deep learning and artificial intelligence. Stan Bileschi  is the technical lead for Google's TensorFlow Usability team, which built the TensorFlow Layers API. Eric Nielsen  is a senior software engineer on the Google Brain team.
AuthorShanqing Cai BindingPaperback
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By Oliver Durr
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Oliver Duerr  is professor for data science at the University of Applied Sciences in Konstanz, Germany. Beate Sick  holds a chair for applied statistics at ZHAW, and works as a researcher and lecturer at the University of Zurich, and as a lecturer at ETH Zurich.  Elvis Murina  is a research assistant, responsible for the extensive exercises that accompany this book.
AuthorOliver Durr BindingPaperback
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By Stephan Raaijmakers
$5999 $4379
Stephan Raaijmakers  is professor of Communicative AI at Leiden University and a senior scientist at The Netherlands Organization for Applied Scientific Research (TNO).
AuthorStephan Raaijmakers BindingPaperback
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By ​M.G. Sumithra, Rajesh Kumar Dhanaraj, Mariofanna Milanova, Balamurugan Balusamy, Chandran Venkatesan
$19495 $15596
This product will be shipped on 30-06-2023
M. G. Sumithra, PhD,   is a professor at Anna University Chennai, India. With 25 years of teaching experience, she has published 66 technical papers in refereed journals, 3 book chapters and 129 research papers in national and international conferences. Rajesh Kumar Dhanaraj, PhD , is a Professor in the School of Computing Science and Engineering at Galgotias University, Greater Noida, India.   Mariofanna Milanova, PhD,  is a professor in the Department of Computer Science at University of Arkansas, Little Rock. Balamurugan Balusamy, PhD , is a professor in the School of Computing Science and Engineering, Galgotias University, Greater Noida, India. V. Chandran holds an M.E degree in VLSI Design at Government College of Technology, Coimbatore and is a Nvidia Certified Instructor for Deep learning for Computer Vison.
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By Bharat Sikka
In stock
$996 $847
Who this book is for This book is for the readers who aspire to gain a strong fundamental understanding of how to infuse deep learning into computer vision and image processing applications. Readers are expected to have intermediate Python skills. No previous knowledge of PyTorch and Computer Vision is required.
AuthorBharat Sikka BindingPaperback
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By Mohamed Sabri
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$1114 $947
Who this book is for This book is for data professionals, data scientists, students, or those who are new to the field who wish to stay on top of industry jargon and terminologies used in the field of data science.
AuthorMohamed Sabri BindingPaperback
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Aurélien Géron is a Machine Learning consultant. A former Googler, he led YouTube's video classification team from 2013 to 2016. He was also a founder and CTO of Wifirst from 2002 to 2012, a leading Wireless ISP in France, and a founder and CTO of Polyconseil in 2001, a telecom consulting firm.
AuthorAurélien Géron BindingPaperback
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By Thushan Ganegedara
$6999 $5762
Thushan Ganegedara  is a data scientist with QBE. He holds a PhD in machine learning from the University of Sydney and he has worked with TensorFlow for almost 5 years. Thushan is also one of the most active answer providers for TensorFlow and TensorFlow2.0 tags on Stackoverflow, a DataCamp instructor, and has authored a book and video course on NLP with TensorFlow.
AuthorThushan Ganegedara BindingPaperback
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By Francois Chollet, Tomasz Kalinowski, J. J. Allaire
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$5999 $5000
François Chollet  is a software engineer at Google and creator of Keras. Tomasz Kalinowski  is a software engineer at RStudio and maintainer of the Keras and Tensorflow R packages. J.J. Allaire  is the founder of RStudio, the creator of the R interfaces to TensorFlow and Keras, and the author of the first edition of this book.
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