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出版日:2021/12/21 作者:François Chollet  出版社:MANNING PUBN  裝訂:平裝
In Deep Learning with Python, Second Edition, updated from the original bestseller with over 50% new content, you'll explore challenging concepts and practice applications in computer vision, natural-language processing, and generative models. The bestseller revised Deep Learning with Python, Second Edition is a comprehensive introduction to the field of deep learning using Python and the powerful Keras library, written by the creator of Keras himself. This revised edition has been updated with new chapters, new tools, and cutting-edge techniques drawn from the latest research. In Deep Learning with Python, Second Edition, updated from the original bestseller with over 50% new content, you'll explore challenging concepts and practice applications in computer vision, natural-language processing, and generative models, building your understanding through practical examples and intuitive explanations that make the complexities of deep learning easily accessible. Purchase of the print book
優惠價: 1 3000
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Deep Learning with Python: Learn Best Practices of Deep Learning Models with Pytorch
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出版日:2021/04/14 作者:Nikhil Ketkar  出版社:Apress  裝訂:平裝
Master the practical aspects of implementing deep learning solutions with PyTorch, using a hands-on approach to understanding both theory and practice. This updated edition will prepare you for applying deep learning to real world problems with a sound theoretical foundation and practical know-how with PyTorch, a platform developed by Facebook's Artificial Intelligence Research Group.You'll start with a perspective on how and why deep learning with PyTorch has emerged as an path-breaking framework with a set of tools and techniques to solve real-world problems. Next, the book will ground you with the mathematical fundamentals of linear algebra, vector calculus, probability and optimization. Having established this foundation, you'll move on to key components and functionality of PyTorch including layers, loss functions and optimization algorithms. You'll also gain an understanding of Graphical Processing Unit (GPU) based computation, which is essential for training deep learning models
優惠價: 1 1444
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Python: 2 Manuscript: Deep Learning with Python, Python for Data Analysis
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出版日:2021/02/24 作者:Daniel Géron  出版社:Lightning Source Inc  裝訂:平裝
優惠價: 1 1519
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Python: 2 Manuscript: Deep Learning with Python, Python for Data Analysis
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出版日:2021/02/24 作者:Daniel Géron  出版社:Lightning Source Inc  裝訂:精裝
優惠價: 1 2279
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Python: 2 Manuscript: Deep Learning with Python, Python for Data Analysis
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出版日:2021/01/19 作者:Daniel Géron  出版社:Lightning Source Inc  裝訂:精裝
優惠價: 1 1367
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Python: 2 Manuscript: Deep Learning with Python, Python for Data Analysis
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出版日:2021/01/12 作者:Daniel Géron  出版社:Lightning Source Inc  裝訂:平裝
優惠價: 1 1139
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Applied Neural Networks with Tensorflow 2: API Oriented Deep Learning with Python
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出版日:2020/12/15 作者:Orhan Gazi Yalçı; n  出版社:Apress  裝訂:平裝
優惠價: 1 2090
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出版日:2020/11/10 作者:Oliver Duerr; Beate Sick; Elvis Murina  出版社:PBKMANGN  裝訂:平裝
優惠價: 1 2500
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Python Machine Learning: A Complete Guide for Beginners on Machine Learning and Deep Learning with Python
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出版日:2020/11/13 作者:Andrew Park  出版社:Lightning Source Inc  裝訂:精裝
優惠價: 1 1328
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Python: The Complete Crash Course to Learn Python in One Week Machine Learning and Deep Learning with Python with Hands-On Exe
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Python: The Complete Crash Course to Learn Python in One Week Machine Learning and Deep Learning with Python with Hands-On Exe
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出版日:2021/12/01 作者:Mehdi Ghayoumi  出版社:CRC PR INC  裝訂:精裝
Deep Learning in Practice helps you learn how to develop and optimize a model for your projects using Deep Learning (DL) methods and architectures.Key features: Demonstrates a quick review on Python, NumPy, and TensorFlow fundamentals.Explains and provides examples of deploying TensorFlow and Keras in several projects.Explains the fundamentals of Artificial Neural Networks (ANNs).Presents several examples and applications of ANNs.Learning the most popular DL algorithms features.Explains and provides examples for the DL algorithms that are presented in this book.Analyzes the DL network's parameter and hyperparameters.Reviews state-of-the-art DL examples.Necessary and main steps for DL modeling.Implements a Virtual Assistant Robot (VAR) using DL methods.Necessary and fundamental information to choose a proper DL algorithm.Gives instructions to learn how to optimize your DL model IN PRACTICE.This book is useful for undergraduate and graduate students, as well as practitioners in industry
若需訂購本書,請電洽客服 02-25006600[分機130、131]。
出版日:2021/10/29 作者:Ben Auffarth  出版社:PACKT PUB  裝訂:平裝
Become proficient in deriving insights from time-series data and analyzing a model's performanceKey Features: Explore popular and modern machine learning methods including the latest online and deep learning algorithmsLearn to increase the accuracy of your predictions by matching the right model with the right problemMaster time-series via real-world case studies on operations management, digital marketing, finance, and healthcareBook Description: Machine learning has emerged as a powerful tool to understand hidden complexities in time-series datasets, which frequently need to be analyzed in areas as diverse as healthcare, economics, digital marketing, and social sciences. These datasets are essential for forecasting and predicting outcomes or for detecting anomalies to support informed decision making.This book covers Python basics for time-series and builds your understanding of traditional autoregressive models as well as modern non-parametric models. You will become confident with
優惠價: 1 3119
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Deep Learning for Beginners ― A Python-based Introduction
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出版日:2021/02/23 作者:Ron Kneusel  出版社:No Starch Pr  裝訂:平裝
Practical Deep Learning teaches total beginners how to build the datasets and models needed to train neural networks for your own DL projects.If you've been curious about machine learning but didn't k
優惠價: 79 1801
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Deep Learning ― A Visual Approach
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出版日:2021/02/16 作者:Andrew Glassner  出版社:No Starch Pr  裝訂:精裝
A richly-illustrated, full-color introduction to deep learning that offers visual and conceptual explanations instead of equations. You'll learn how to use key deep learning algorithms without the nee
優惠價: 79 3002
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出版日:2021/01/25 作者:Joseph Mining  出版社:Lightning Source Inc  裝訂:精裝
The world of machine learning is changing all the time. It is so amazing the idea that we are able to take a computer and let it learn as it goes. Without having to write out all of the codes that we need for every situation out there or every input that the user may pick, we are able to write out codes in machine learning, even with Python, in order to let the computer or device learn and make decisions on its own.This guidebook is going to take a closer look at how Python machine learning is able to work, as well as how you can use some of the tools and techniques that come with this process for your own needs. When you are interested in learning more about what machine learning is all about, as well as how you can use a part of the coding from Python inside of this process, then this guidebook is the tool for you Some of the topics that we will explore when we go through this guidebook will include: Understanding some of the basics of machine learning;Some of the different parts tha
Deep Learning on Graphs
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出版日:2021/08/31 作者:Yao Ma  出版社:Cambridge Univ Pr  裝訂:精裝
Deep learning on graphs has become one of the hottest topics in machine learning. The book consists of four parts to best accommodate our readers with diverse backgrounds and purposes of reading. Part 1 introduces basic concepts of graphs and deep learning; Part 2 discusses the most established methods from the basic to advanced settings; Part 3 presents the most typical applications including natural language processing, computer vision, data mining, biochemistry and healthcare; and Part 4 describes advances of methods and applications that tend to be important and promising for future research. The book is self-contained, making it accessible to a broader range of readers including (1) senior undergraduate and graduate students; (2) practitioners and project managers who want to adopt graph neural networks into their products and platforms; and (3) researchers without a computer science background who want to use graph neural networks to advance their disciplines.
優惠價: 9 2632
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Natural Language Processing:A Machine Learning Perspective
90 折
出版日:2021/01/07 作者:Yue Zhang  出版社:Cambridge Univ Pr  裝訂:精裝
With a machine learning approach and less focus on linguistic details, this gentle introduction to natural language processing develops fundamental mathematical and deep learning models for NLP under a unified framework. NLP problems are systematically organised by their machine learning nature, including classification, sequence labelling, and sequence-to-sequence problems. Topics covered include statistical machine learning and deep learning models, text classification and structured prediction models, generative and discriminative models, supervised and unsupervised learning with latent variables, neural networks, and transition-based methods. Rich connections are drawn between concepts throughout the book, equipping students with the tools needed to establish a deep understanding of NLP solutions, adapt existing models, and confidently develop innovative models of their own. Featuring a host of examples, intuition, and end of chapter exercises, plus sample code available as an onli
優惠價: 9 3131
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Deep Learning in a Disorienting World
90 折
出版日:2020/01/31 作者:Jon F. Wergin  出版社:Cambridge Univ Pr  裝訂:平裝
Much has been written about the escalating intolerance of worldviews other than one's own. Reasoned arguments based on facts and data seem to have little impact in our increasingly post-truth culture dominated by social media, fake news, tribalism, and identity politics. Recent advances in the study of human cognition, however, offer insights on how to counter these troubling social trends. In this book, psychologist Jon F. Wergin calls upon recent research in learning theory, social psychology, politics, and the arts to show how a deep learning mindset can be developed in both oneself and others. Deep learning is an acceptance that our understanding of the world around us is only temporary and is subject to constant scrutiny. Someone who is committed to learning deeply does not simply react to experiences, but engages fully with that experience, knowing that the inevitable disquietude is what leads to efficacy in the world.
優惠價: 9 1619
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Deep Learning in a Disorienting World
90 折
出版日:2020/01/31 作者:Jon F. Wergin  出版社:Cambridge Univ Pr  裝訂:精裝
Much has been written about the escalating intolerance of worldviews other than one's own. Reasoned arguments based on facts and data seem to have little impact in our increasingly post-truth culture dominated by social media, fake news, tribalism, and identity politics. Recent advances in the study of human cognition, however, offer insights on how to counter these troubling social trends. In this book, psychologist Jon F. Wergin calls upon recent research in learning theory, social psychology, politics, and the arts to show how a deep learning mindset can be developed in both oneself and others. Deep learning is an acceptance that our understanding of the world around us is only temporary and is subject to constant scrutiny. Someone who is committed to learning deeply does not simply react to experiences, but engages fully with that experience, knowing that the inevitable disquietude is what leads to efficacy in the world.
若需訂購本書,請電洽客服 02-25006600[分機130、131]。
Deep Learning in Science
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出版日:2021/05/31 作者:Pierre Baldi  出版社:Cambridge Univ Pr  裝訂:精裝
This is the first rigorous, self-contained treatment of the theory of deep learning. Starting with the foundations of the theory and building it up, this is essential reading for any scientists, instructors, and students interested in artificial intelligence and deep learning. It provides guidance on how to think about scientific questions, and leads readers through the history of the field and its fundamental connections to neuroscience. The author discusses many applications to beautiful problems in the natural sciences, in physics, chemistry, and biomedicine. Examples include the search for exotic particles and dark matter in experimental physics, the prediction of molecular properties and reaction outcomes in chemistry, and the prediction of protein structures and the diagnostic analysis of biomedical images in the natural sciences. The text is accompanied by a full set of exercises at different difficulty levels and encourages out-of-the-box thinking.
優惠價: 9 2924
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Real-world Python ― A Hacker's Guide to Solving Problems With Code
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出版日:2020/10/13 作者:Lee Vaughan  出版社:No Starch Pr  裝訂:平裝
A project-based approach to learning Python programming for beginners. Intriguing projects teach you how to tackle challenging problems with code.You've mastered the basics. Now you're ready to explor
優惠價: 79 1201
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出版日:2020/08/25 作者:Basilio de Braganca Pereira; Calyampudi Radhakrishna Rao and Fabio Borges de Oliveira  出版社:Chapman & Hall  裝訂:精裝
This book introduces artificial neural networks to students and professionals. It covers the theory and applications in statistical learning methods with concrete Python code examples.
若需訂購本書,請電洽客服 02-25006600[分機130、131]。
出版日:2020/08/17 作者:Shrirang Ambaji Kulkarni; Varadrah P. Gurupur and Steven L. Fernandes  出版社:Chapman & Hall  裝訂:精裝
This book introduces Raspberry Pi, using real world applications in computer vision, machine learning, and deep learning. It provides a detailed, step-by-step, approach to application development for
若需訂購本書,請電洽客服 02-25006600[分機130、131]。
Python機器學習第三版(下)
90 折
出版日:2020/10/08 作者:Sebastian Raschka; Vahid Mirjalili  出版社:博碩文化  裝訂:平裝
Python機器學習第三版(下) Python Machine Learning - Third Edition 第三版-最新修訂版,新增TensorFlow 2、GAN和強化學習等實用內容 使用Python的scikit-learn和TensorFlow 2融會貫通機器學習與深度學習 循序漸進、由淺入深,好評熱銷再進化!最新修訂的《Python機器學習第三版》是一本不容錯過的全方位指南,也是讀者
Python機器學習第三版(上)
90 折
出版日:2020/09/16 作者:Sebastian Raschka; Vahid Mirjalili  出版社:博碩文化  裝訂:平裝
Python機器學習第三版(上) Python Machine Learning - Third Edition 第三版-最新修訂版,新增TensorFlow 2、GAN和強化學習等實用內容 使用Python的scikit-learn和TensorFlow 2融會貫通機器學習與深度學習 循序漸進、由淺入深,好評熱銷再進化!最新修訂的《Python機器學習第三版》是一本不容錯過的全方位指南,也是讀者
Machine Learning for Speaker Recognition
90 折
出版日:2020/07/31 作者:Man-Wai Mak  出版社:Cambridge Univ Pr  裝訂:精裝
This book will help readers understand fundamental and advanced statistical models and deep learning models for robust speaker recognition and domain adaptation. This useful toolkit enables readers to apply machine learning techniques to address practical issues, such as robustness under adverse acoustic environments and domain mismatch, when deploying speaker recognition systems. Presenting state-of-the-art machine learning techniques for speaker recognition and featuring a range of probabilistic models, learning algorithms, case studies, and new trends and directions for speaker recognition based on modern machine learning and deep learning, this is the perfect resource for graduates, researchers, practitioners and engineers in electrical engineering, computer science and applied mathematics.
若需訂購本書,請電洽客服 02-25006600[分機130、131]。
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