Principles and Labs for Deep Learning

Written By Shih-Chia Huang
Principles and Labs for Deep Learning
  • Publsiher : Academic Press
  • Release : 06 July 2021
  • ISBN : 0323901999
  • Pages : 366 pages
  • Rating : 4/5 from 21 reviews
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Read or download book entitled Principles and Labs for Deep Learning written by Shih-Chia Huang which was release on 06 July 2021, this book published by Academic Press. Available in PDF, EPUB and Kindle Format. Book excerpt: Principles and Labs for Deep Learning provides the knowledge and techniques needed to help readers design and develop deep learning models. Deep Learning techniques are introduced through theory, comprehensively illustrated, explained through the TensorFlow source code examples, and analyzed through the visualization of results. The structured methods and labs provided by Dr. Huang and Dr. Le enable readers to become proficient in TensorFlow to build deep Convolutional Neural Networks (CNNs) through custom APIs, high-level Keras APIs, Keras Applications, and TensorFlow Hub. Each chapter has one corresponding Lab with step-by-step instruction to help the reader practice and accomplish a specific learning outcome. Deep Learning has been successfully applied in diverse fields such as computer vision, audio processing, robotics, natural language processing, bioinformatics and chemistry. Because of the huge scope of knowledge in Deep Learning, a lot of time is required to understand and deploy useful, working applications, hence the importance of this new resource. Both theory lessons and experiments are included in each chapter to introduce the techniques and provide source code examples to practice using them. All Labs for this book are placed on GitHub to facilitate the download. The book is written based on the assumption that the reader knows basic Python for programming and basic Machine Learning. Introduces readers to the usefulness of neural networks and Deep Learning methods Provides readers with in-depth understanding of the architecture and operation of Deep Convolutional Neural Networks Demonstrates the visualization needed for designing neural networks Provides readers with an in-depth understanding of regression problems, binary classification problems, multi-category classification problems, Variational Auto-Encoder, Generative Adversarial Network, and Object detection

Principles and Labs for Deep Learning

Principles and Labs for Deep Learning
  • Author : Shih-Chia Huang,Trung-Hieu Le
  • Publisher : Academic Press
  • Release Date : 2021-07-06
  • Total pages : 366
  • ISBN : 0323901999
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Summary : Principles and Labs for Deep Learning provides the knowledge and techniques needed to help readers design and develop deep learning models. Deep Learning techniques are introduced through theory, comprehensively illustrated, explained through the TensorFlow source code examples, and analyzed through the visualization of results. The structured methods and labs provided ...

The Principles of Deep Learning Theory

The Principles of Deep Learning Theory
  • Author : Daniel A. Roberts,Sho Yaida,Boris Hanin
  • Publisher : Cambridge University Press
  • Release Date : 2022-05-26
  • Total pages : 212
  • ISBN : 0323901999
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Summary : This textbook establishes a theoretical framework for understanding deep learning models of practical relevance. With an approach that borrows from theoretical physics, Roberts and Yaida provide clear and pedagogical explanations of how realistic deep neural networks actually work. To make results from the theoretical forefront accessible, the authors eschew the ...

Principles Of Artificial Neural Networks Basic Designs To Deep Learning 4th Edition

Principles Of Artificial Neural Networks  Basic Designs To Deep Learning  4th Edition
  • Author : Graupe Daniel
  • Publisher : World Scientific
  • Release Date : 2019-03-15
  • Total pages : 440
  • ISBN : 0323901999
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Summary : The field of Artificial Neural Networks is the fastest growing field in Information Technology and specifically, in Artificial Intelligence and Machine Learning.This must-have compendium presents the theory and case studies of artificial neural networks. The volume, with 4 new chapters, updates the earlier edition by highlighting recent developments in Deep-Learning ...

Machine Learning and Principles and Practice of Knowledge Discovery in Databases

Machine Learning and Principles and Practice of Knowledge Discovery in Databases
  • Author : Michael Kamp
  • Publisher : Springer Nature
  • Release Date : 2021
  • Total pages : 895
  • ISBN : 0323901999
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Summary : This two-volume set constitutes the refereed proceedings of the workshops which complemented the 21th Joint European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD, held in September 2021. Due to the COVID-19 pandemic the conference and workshops were held online. The 104 papers were thoroughly reviewed and selected from 180 ...

Clinical Herbal Prescriptions Principles And Practices Of Herbal Formulations From Deep Learning Health Insurance Herbal Prescription Big Data

Clinical Herbal Prescriptions  Principles And Practices Of Herbal Formulations From Deep Learning Health Insurance Herbal Prescription Big Data
  • Author : Sun-chong Wang
  • Publisher : World Scientific
  • Release Date : 2019-01-22
  • Total pages : 520
  • ISBN : 0323901999
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Summary : Since AlphaGo defeated Ke Jie (who was then ranked 1st among all human players worldwide) May 2017, the art of Go (otherwise known as Weiqi) has entered a new era. Similarly, if we apply artificial intelligence (AI) to herbal medicine, the art of herbal prescription can experience a game change too. ...

Principles Of Quantum Artificial Intelligence Quantum Problem Solving And Machine Learning Second Edition

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  • Author : Andreas Miroslaus Wichert
  • Publisher : World Scientific
  • Release Date : 2020-07-08
  • Total pages : 496
  • ISBN : 0323901999
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Summary : This unique compendium presents an introduction to problem solving, information theory, statistical machine learning, stochastic methods and quantum computation. It indicates how to apply quantum computation to problem solving, machine learning and quantum-like models to decision making — the core disciplines of artificial intelligence.Most of the chapters were rewritten and ...

Principles and Theory for Data Mining and Machine Learning

Principles and Theory for Data Mining and Machine Learning
  • Author : Bertrand Clarke,Ernest Fokoue,Hao Helen Zhang
  • Publisher : Springer Science & Business Media
  • Release Date : 2009-07-21
  • Total pages : 786
  • ISBN : 0323901999
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Summary : Extensive treatment of the most up-to-date topics Provides the theory and concepts behind popular and emerging methods Range of topics drawn from Statistics, Computer Science, and Electrical Engineering...

Statistical Modelling and Machine Learning Principles for Bioinformatics Techniques Tools and Applications

Statistical Modelling and Machine Learning Principles for Bioinformatics Techniques  Tools  and Applications
  • Author : K. G. Srinivasa,G. M. Siddesh,S. R. Manisekhar
  • Publisher : Springer Nature
  • Release Date : 2020-01-30
  • Total pages : 317
  • ISBN : 0323901999
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Summary : This book discusses topics related to bioinformatics, statistics, and machine learning, presenting the latest research in various areas of bioinformatics. It also highlights the role of computing and machine learning in knowledge extraction from biological data, and how this knowledge can be applied in fields such as drug design, health ...

FIRST Framework 5 Domains 15 Principles Design Facilitate Active Deep Learner eXperience Volume 1 1st Edition

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  • Author : Mohamed M. Bahgat
  • Publisher : Mohamed M. Bahgat
  • Release Date : 2018-02-08
  • Total pages : 166
  • ISBN : 0323901999
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Summary : No doubt learning is a subject that has been addressed by many books and workshops, with the core interest mostly revolving around the content and how to make it unique, relevant, concise, etc. Other books and courses would rather introduce new/creative techniques for better engaging or getting the best ...

Adversarial Machine Learning

Adversarial Machine Learning
  • Author : Anthony D. Joseph,Blaine Nelson,Benjamin I. P. Rubinstein,J. D. Tygar
  • Publisher : Cambridge University Press
  • Release Date : 2018-04-30
  • Total pages : 338
  • ISBN : 0323901999
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Summary : This study allows readers to get to grips with the conceptual tools and practical techniques for building robust machine learning in the face of adversaries....

Deep Learning Machine Learning and IoT in Biomedical and Health Informatics

Deep Learning  Machine Learning and IoT in Biomedical and Health Informatics
  • Author : Sujata Dash,Subhendu Kumar Pani,Joel J. P. C. Rodrigues,Babita Majhi
  • Publisher : CRC Press
  • Release Date : 2022-02-11
  • Total pages : 382
  • ISBN : 0323901999
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Summary : Biomedical and Health Informatics is an important field that brings tremendous opportunities and helps address challenges due to an abundance of available biomedical data. This book examines and demonstrates state-of-the-art approaches for IoT and Machine Learning based biomedical and health related applications. This book aims to provide computational methods for ...

Machine Learning for Business Analytics

Machine Learning for Business Analytics
  • Author : Hemachandran K,Sayantan Khanra,Raul V. Rodriguez,Juan Jaramillo
  • Publisher : CRC Press
  • Release Date : 2022-07-21
  • Total pages : 168
  • ISBN : 0323901999
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Summary : Machine Learning is an integral tool in a business analyst’s arsenal because the rate at which data is being generated from different sources is increasing and working on complex unstructured data is becoming inevitable. Data collection, data cleaning, and data mining are rapidly becoming more difficult to analyze than ...

Cases on Applying Knowledge Economy Principles for Economic Growth in Developing Nations

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  • Author : Piaggesi, Danilo,Landazuri, Helena,Jia, Bo
  • Publisher : IGI Global
  • Release Date : 2022-01-21
  • Total pages : 327
  • ISBN : 0323901999
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Summary : The knowledge economy is the added non-monetary value that society accrues from increased access to data, information, and knowledge in the new, globally connected world. ICT and technology innovation are paving the way for significant economic development opportunities for countries that have embarked in a concerted effort to model their ...

Probabilistic Machine Learning

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  • Author : Kevin P. Murphy
  • Publisher : MIT Press
  • Release Date : 2022-02-01
  • Total pages : 864
  • ISBN : 0323901999
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Summary : A detailed and up-to-date introduction to machine learning, presented through the unifying lens of probabilistic modeling and Bayesian decision theory. This book offers a detailed and up-to-date introduction to machine learning (including deep learning) through the unifying lens of probabilistic modeling and Bayesian decision theory. The book covers mathematical background (...

Principles of Adaptive Filters and Self learning Systems

Principles of Adaptive Filters and Self learning Systems
  • Author : Anthony Zaknich
  • Publisher : Springer Science & Business Media
  • Release Date : 2006-03-30
  • Total pages : 386
  • ISBN : 0323901999
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Summary : Teaches students about classical and nonclassical adaptive systems within one pair of covers Helps tutors with time-saving course plans, ready-made practical assignments and examination guidance The recently developed "practical sub-space adaptive filter" allows the reader to combine any set of classical and/or non-classical adaptive systems to form a powerful ...