introduction to deep learning

Introduction to Deep Learning for Healthcare【電子書籍】 Cao XiaoDeep Learning for Beginners A Comprehensive Introduction of Deep Learning Fundamentals for Beginners to Understanding Frameworks, Neural Networks, Large Datasets, and Creative Applications with Ease【電子書籍】 Steven Cooper深層強化学習入門 / 原タイトル:An Introduction to Deep Reinforcement Learning 本/雑誌 / VincentFrancois‐Lavet/著 PeterHenderson/著 RiashatIslam/著 MarcG.Bellemare/著 JoellePineau/著 松原崇充/監訳 井尻善久/訳 浜屋政志/訳Neural Networks for Beginners Introduction to Machine Learning and Deep Learning【電子書籍】 daniel HustonAn Introduction to Artificial Psychology Application Fuzzy Set Theory and Deep Machine Learning in Psychological Research using R【電子書籍】 Hojjatollah FarahaniIntroduction to Deep Learning and Neural Networks with Python A Practical Guide【電子書籍】 Ahmed Fawzy GadARTIFICIAL INTELLIGENCE FOR BEGINNERS An Introduction to Machine Learning, Neural Networks, and Deep Learning (2023 Guide for Beginners)【電子書籍】 Astrid Howe洋書 Apress Paperback, Introduction to Deep Learning Using R: A Step-by-Step Guide to Learning and Implementing Deep Learning Models Using RBeginning with Machine Learning The Ultimate Introduction to Machine Learning, Deep Learning, Scikit-learn, and TensorFlow (English Edition)【電子書籍】 Dr. Amit DuaDeep Learning for Beginners: A Comprehensive Introduction of Deep Learning Fundamentals for Beginners to Understanding Frameworks, Neural Networks, Large Datasets, and Creative Applications with Ease【電子書籍】 Steven CooperAI Crash Course A fun and hands-on introduction to machine learning, reinforcement learning, deep learning, and artificial intelligence with Python【電子書籍】 Hadelin de PontevesIntroduction to Deep Learning From Logical Calculus to Artificial Intelligence【電子書籍】 Sandro SkansiDemystifying Deep Learning An Introduction to the Mathematics of Neural Networks【電子書籍】 Douglas J. Santry洋書 Paperback, An Introduction to Deep Reinforcement Learning (Foundations and Trends(r) in Machine Learning)TensorFlow 2.x in the Colaboratory Cloud An Introduction to Deep Learning on Google’s Cloud Service【電子書籍】 David Paper洋書 Introduction to Deep Learning: From Logical Calculus to Artificial Intelligence (Undergraduate Topics in Computer Science)Introduction to Deep Learning Business Applications for Developers From Conversational Bots in Customer Service to Medical Image Processing【電子書籍】 Armando Vieira【中古】【輸入品 未使用】Introduction to Deep Learning: From Logical Calculus to Artificial Intelligence (Undergraduate Topics in Computer Science)Introduction to Deep Learning【電子書籍】 Eugene CharniakIntroduction to Deep Learning Using R A Step-by-Step Guide to Learning and Implementing Deep Learning Models Using R【電子書籍】 Taweh Beysolow II

Introduction to Deep Learning for Healthcare【電子書籍】[ Cao Xiao ]

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  • ＜p＞This textbook presents deep learning models and their healthcare applications. It focuses on rich health data and deep learning models that can effectively model health data. Healthcare data: Among all healthcare technologies, electronic health records (EHRs) had vast adoption and a significant impact on healthcare delivery in recent years. One crucial benefit of EHRs is to capture all the patient encounters with rich multi-modality data. Healthcare data include both structured and unstructured information. Structured data include various medical codes for diagnoses and procedures, lab results, and medication information. Unstructured data contain 1) clinical notes as text, 2) medical imaging data such as X-rays, echocardiogram, and magnetic resonance imaging (MRI), and 3) time-series data such as the electrocardiogram (ECG) and electroencephalogram (EEG). Beyond the data collected during clinical visits, patient self-generated/reported data start to grow thanks to wearable sen...

    • Deep Learning for Beginners A Comprehensive Introduction of Deep Learning Fundamentals for Beginners to Understanding Frameworks, Neural Networks, Large Datasets, and Creative Applications with Ease【電子書籍】[ Steven Cooper ]

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  • ＜p＞☆★The Best Deep Learning Book for Beginners★☆＜/p＞ ＜p＞＜strong＞If you are looking for a complete beginners guide to learn deep learning with examples, in just a few hours, then you need to continue reading.＜/strong＞＜/p＞ ＜p＞This book delves into the basics of deep learning for those who are enthusiasts concerning all things machine learning and artificial intelligence. For those who have seen movies which show computer systems taking over the world like, Terminator, or benevolent systems that watch over the population, i.e. Person of Interest, this should be right up your alley.＜/p＞ ＜p＞This book will give you the basics of what deep learning entails. That means frameworks used by coders and significant components and tools used in deep learning, that enable facial recognition, speech recognition, and virtual assistance. Yes, deep learning provides the tools through which systems like Siri became possible.＜/p＞ ＜p＞＜strong＞★★ Grab your copy today and learn ★★＜/...

    • 深層強化学習入門 / 原タイトル:An Introduction to Deep Reinforcement Learning[本/雑誌] / VincentFrancois‐Lavet/著 PeterHenderson/著 RiashatIslam/著 MarcG.Bellemare/著 JoellePineau/著 松原崇充/監訳 井尻善久/訳 浜屋政志/訳

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  • ご注文前に必ずご確認ください＜商品説明＞＜収録内容＞はじめに機械学習と深層学習強化学習の基礎価値ベース手法による深層強化学習方策勾配法による深層強化学習モデルベース手法による深層強化学習汎化性オンライン問題に特有の課題深層強化学習のベンチマークMDPを超える深層強化学習深層強化学習の展望結論＜商品詳細＞商品番号：NEOBK-2605006VincentFrancois Lavet / Cho PeterHenderson / Cho RiashatIslam / Cho MarcG. Bellemare / Cho JoellePineau / Cho Matsubara Takashi Takashi / Kanyaku Ijiri Yoshihisa / Yaku Hamaya Masashi / Yaku / Shinso Kyoka Gakushu Nyumon / Original Title: an Introduction to Deep Reinforcement Learningメディア：本/雑誌重量：340g発売日：2021/04JAN：9784320124721深層強化学習入門 / 原タイトル:An Introduction to Deep Reinforcement Learning[本/雑誌] / VincentFrancois‐Lavet/著 PeterHenderson/著 RiashatIslam/著 MarcG.Bellemare/著 JoellePineau/著 松原崇充/監訳 井尻善久/訳 浜屋政志/訳2021/04発売

    • Neural Networks for Beginners Introduction to Machine Learning and Deep Learning【電子書籍】[ daniel Huston ]

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  • ＜p＞"Neural Networks for Beginners" is a beginner-friendly guide to understanding the basics of neural networks, machine learning, and deep learning. Written in simple language, this book provides a comprehensive introduction to the key concepts and techniques used in neural networks. Starting with an overview of the history and importance of neural networks, the book covers the basics of machine learning and deep learning, including their differences and applications. It then delves into the different types of neural networks, their architectures, and how they are trained and optimized. The book also provides real-world examples of successful neural network applications in various fields, such as healthcare, finance, and technology. It explains how neural networks are used in practical applications, such as image recognition, speech recognition, and natural language processing. "Neural Networks for Beginners" is perfect for anyone with no prior knowledge of neural networks who wan...

    • An Introduction to Artificial Psychology Application Fuzzy Set Theory and Deep Machine Learning in Psychological Research using R【電子書籍】[ Hojjatollah Farahani ]

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  • ＜p＞Artificial Psychology (AP) is a highly multidisciplinary field of study in psychology. AP tries to solve problems which occur when psychologists do research and need a robust analysis method. Conventional statistical approaches have deep rooted limitations. These approaches are excellent on paper but often fail to model the real world. Mind researchers have been trying to overcome this by simplifying the models being studied. This stance has not received much practical attention recently. Promoting and improving artificial intelligence helps mind researchers to find a holistic model of mental models. This development achieves this goal by using multiple perspectives and multiple data sets together with interactive, and realistic models. In this book, the methodology of approximate inference in psychological research from a theoretical and practical perspective has been considered. Quantitative variable-oriented methodology and qualitative case-oriented methods are both used to ...

    • Introduction to Deep Learning and Neural Networks with Python? A Practical Guide【電子書籍】[ Ahmed Fawzy Gad ]

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  • ＜p＞＜em＞Introduction to Deep Learning and Neural Networks with Python?: A Practical Guide＜/em＞ is an intensive step-by-step guide for neuroscientists to fully understand, practice, and build neural networks. Providing math and Python? code examples to clarify neural network calculations, by book’s end readers will fully understand how neural networks work starting from the simplest model Y=X and building from scratch. Details and explanations are provided on how a generic gradient descent algorithm works based on mathematical and Python? examples, teaching you how to use the gradient descent algorithm to manually perform all calculations in both the forward and backward passes of training a neural network.＜/p＞ ＜ul＞ ＜li＞Examines the practical side of deep learning and neural networks＜/li＞ ＜li＞Provides a problem-based approach to building artificial neural networks using real data＜/li＞ ＜li＞Describes Python? functions and features for neuroscientists＜/li＞ ＜li＞Use...

    • ARTIFICIAL INTELLIGENCE FOR BEGINNERS An Introduction to Machine Learning, Neural Networks, and Deep Learning (2023 Guide for Beginners)【電子書籍】[ Astrid Howe ]

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  • ＜p＞＜strong＞Artificial Intelligence (AI) has become one of the most exciting＜/strong＞ and ＜strong＞rapidly growing fields in technology＜/strong＞, with applications ranging from self-driving cars to virtual personal assistants. However, ＜strong＞for those who are new to the subject＜/strong＞, the vast amount ＜strong＞of information can be overwhelming＜/strong＞.＜/p＞ ＜p＞＜strong＞This book is designed to provide an accessible introduction to AI for beginners＜/strong＞, breaking down complex concepts into easy-to-understand language.＜/p＞ ＜p＞＜em＞＜strong＞In this book, you will learn:＜/strong＞＜/em＞＜/p＞ ＜ul＞ ＜li＞＜strong＞The basics of machine learning, including supervised and unsupervised learning＜/strong＞＜/li＞ ＜li＞The fundamentals of neural networks and how they work＜/li＞ ＜li＞＜strong＞The concept of deep learning and how it is transforming various industries＜/strong＞＜/li＞ ＜li＞The different types of AI algorithms and their applications...

    • 洋書 Apress Paperback, Introduction to Deep Learning Using R: A Step-by-Step Guide to Learning and Implementing Deep Learning Models Using R

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  • *** We ship internationally, so do not use a package forwarding service. We cannot ship to a package forwarding company address because of the Japanese customs regulation. If it is shipped and customs office does not let the package go, we do not make a refund. 【注意事項】 *** 特に注意してください。 *** ・個人ではない法人・団体名義での購入はできません。この場合税関で滅却されてもお客様負担になりますので御了承願います。 ・お名前にカタカナが入っている場合法人である可能性が高いため当店システムから自動保留します。カタカナで記載が必要な場合はカタカナ変わりローマ字で記載してください。 ・お名前またはご住所が法人・団体名義（XX株式会社等）、商店名などを含めている場合、または電話番号が個人のものではない場合、税関から法人名義でみなされますのでご注意ください。 ・転送サービス会社への発送もできません。この場合税関で滅却されてもお客様負担になりますので御了承願います。 *** ・注文後品切れや価格変動でキャンセルされる場合がございますので予めご了承願います。 ・当店でご購入された商品は、原則として、「個...

    • Beginning with Machine Learning The Ultimate Introduction to Machine Learning, Deep Learning, Scikit-learn, and TensorFlow (English Edition)【電子書籍】[ Dr. Amit Dua ]

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  • ＜p＞Should I choose supervised learning or reinforcement learning? Which algorithm is best suited for my application? How does deep learning advance the capacities of problem-solving? If you have found yourself asking these questions, this book is specially developed for you. The book will help readers understand the core concepts of machine learning and techniques to evaluate any machine learning model with ease. The book starts with the importance of machine learning by analyzing its impact on the global landscape. The book also covers Supervised and Unsupervised ML along with Reinforcement Learning. In subsequent chapters, the book explores these topics in even greater depth, evaluating the pros and cons of each and exploring important topics such as Bias-Variance Tradeoff, Clustering, and Dimensionality Reduction. The book also explains model evaluation techniques such as Cross-Validation and GridSearchCV. The book also features mind maps which help enhance the learning process...

    • Deep Learning for Beginners: A Comprehensive Introduction of Deep Learning Fundamentals for Beginners to Understanding Frameworks, Neural Networks, Large Datasets, and Creative Applications with Ease【電子書籍】[ Steven Cooper ]

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  • ＜p＞☆★The Best Deep Learning Book For Beginners★☆＜/p＞ ＜p＞＜strong＞If you are looking for a complete beginners guide to learn deep learning with examples, in just a few hours, then you need to continue reading.＜/strong＞＜/p＞ ＜p＞This book delves into the basics of deep learning for those who are enthusiasts concerning all things machine learning and artificial intelligence. For those who have seen movies which show computer systems taking over the world like, Terminator, or benevolent systems that watch over the population, i.e. Person of Interest, this should be right up your alley.＜/p＞ ＜p＞This book will give you the basics of what deep learning entails. That means frameworks used by coders and significant components and tools used in deep learning, that enable facial recognition, speech recognition, and virtual assistance. Yes, deep learning provides the tools through which systems like Siri became possible.＜/p＞ ＜p＞＜strong＞★★ Grab your copy today and learn ★★＜/...

    • AI Crash Course A fun and hands-on introduction to machine learning, reinforcement learning, deep learning, and artificial intelligence with Python【電子書籍】[ Hadelin de Ponteves ]

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  • ＜p＞＜strong＞Unlock the power of artificial intelligence with top Udemy AI instructor Hadelin de Ponteves.＜/strong＞＜/p＞ ＜h4＞Key Features＜/h4＞ ＜ul＞ ＜li＞Learn from friendly, plain English explanations and practical activities＜/li＞ ＜li＞Put ideas into action with 5 hands-on projects that show step-by-step how to build intelligent software＜/li＞ ＜li＞Use AI to win classic video games and construct a virtual self-driving car＜/li＞ ＜/ul＞ ＜h4＞Book Description＜/h4＞ ＜p＞Welcome to the Robot World ... and start building intelligent software now!＜/p＞ ＜p＞Through his best-selling video courses, Hadelin de Ponteves has taught hundreds of thousands of people to write AI software. Now, for the first time, his hands-on, energetic approach is available as a book. Starting with the basics before easing you into more complicated formulas and notation, AI Crash Course gives you everything you need to build AI systems with reinforcement learning and deep learning. Five full...

    • Introduction to Deep Learning From Logical Calculus to Artificial Intelligence【電子書籍】[ Sandro Skansi ]

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  • ＜p＞This textbook presents a concise, accessible and engaging first introduction to deep learning, offering a wide range of connectionist models which represent the current state-of-the-art. The text explores the most popular algorithms and architectures in a simple and intuitive style, explaining the mathematical derivations in a step-by-step manner. The content coverage includes convolutional networks, LSTMs, Word2vec, RBMs, DBNs, neural Turing machines, memory networks and autoencoders. Numerous examples in working Python code are provided throughout the book, and the code is also supplied separately at an accompanying website.＜/p＞ ＜p＞Topics and features: introduces the fundamentals of machine learning, and the mathematical and computational prerequisites for deep learning; discusses feed-forward neural networks, and explores the modifications to these which can be applied to any neural network; examines convolutional neural networks, and the recurrent connections to a feed-...

    • Demystifying Deep Learning An Introduction to the Mathematics of Neural Networks【電子書籍】[ Douglas J. Santry ]

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  • ＜p＞＜strong＞DEMYSTIFYING DEEP LEARNING＜/strong＞＜/p＞ ＜p＞＜strong＞Discover how to train Deep Learning models by learning how to build real Deep Learning software libraries and verification software!＜/strong＞＜/p＞ ＜p＞The study of Deep Learning and Artificial Neural Networks (ANN) is a significant subfield of artificial intelligence (AI) that can be found within numerous fields: medicine, law, financial services, and science, for example. Just as the robot revolution threatened blue-collar jobs in the 1970s, so now the AI revolution promises a new era of productivity for white collar jobs. Important tasks have begun being taken over by ANNs, from disease detection and prevention, to reading and supporting legal contracts, to understanding experimental data, model protein folding, and hurricane modeling. AI is everywhereーon the news, in think tanks, and occupies government policy makers all over the world ーand ANNs often provide the backbone for AI.＜/p＞ ＜p＞Relying on...

    • 洋書 Paperback, An Introduction to Deep Reinforcement Learning (Foundations and Trends(r) in Machine Learning)

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  • *** We ship internationally, so do not use a package forwarding service. We cannot ship to a package forwarding company address because of the Japanese customs regulation. If it is shipped and customs office does not let the package go, we do not make a refund. 【注意事項】 *** 特に注意してください。 *** ・個人ではない法人・団体名義での購入はできません。この場合税関で滅却されてもお客様負担になりますので御了承願います。 ・お名前にカタカナが入っている場合法人である可能性が高いため当店システムから自動保留します。カタカナで記載が必要な場合はカタカナ変わりローマ字で記載してください。 ・お名前またはご住所が法人・団体名義（XX株式会社等）、商店名などを含めている場合、または電話番号が個人のものではない場合、税関から法人名義でみなされますのでご注意ください。 ・転送サービス会社への発送もできません。この場合税関で滅却されてもお客様負担になりますので御了承願います。 *** ・注文後品切れや価格変動でキャンセルされる場合がございますので予めご了承願います。 ・当店でご購入された商品は、原則として、「個...

    • TensorFlow 2.x in the Colaboratory Cloud An Introduction to Deep Learning on Google’s Cloud Service【電子書籍】[ David Paper ]

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  • ＜p＞Use TensorFlow 2.x with Google's Colaboratory (Colab) product that offers a free cloud service for Python programmers. Colab is especially well suited as a platform for TensorFlow 2.x deep learning applications. You will learn Colab’s default install of the most current TensorFlow 2.x along with Colab’s easy access to on-demand GPU hardware acceleration in the cloud for fast execution of deep learning models. This book offers you the opportunity to grasp deep learning in an applied manner with the only requirement being an Internet connection. Everything elseーPython, TensorFlow 2.x, GPU support, and Jupyter Notebooksーis provided and ready to go from Colab.＜/p＞ ＜p＞The book begins with an introduction to TensorFlow 2.x and the Google Colab cloud service. You will learn how to provision a workspace on Google Colab and build a simple neural network application. From there you will progress into TensorFlow datasets and building input pipelines in support of modeling and testin...

    • 洋書 Introduction to Deep Learning: From Logical Calculus to Artificial Intelligence (Undergraduate Topics in Computer Science)

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  • *** We ship internationally, so do not use a package forwarding service. We cannot ship to a package forwarding company address because of the Japanese customs regulation. If it is shipped and customs office does not let the package go, we do not make a refund. 【注意事項】 *** 特に注意してください。 *** ・個人ではない法人・団体名義での購入はできません。この場合税関で滅却されてもお客様負担になりますので御了承願います。 ・お名前にカタカナが入っている場合法人である可能性が高いため当店システムから自動保留します。カタカナで記載が必要な場合はカタカナ変わりローマ字で記載してください。 ・お名前またはご住所が法人・団体名義（XX株式会社等）、商店名などを含めている場合、または電話番号が個人のものではない場合、税関から法人名義でみなされますのでご注意ください。 ・転送サービス会社への発送もできません。この場合税関で滅却されてもお客様負担になりますので御了承願います。 *** ・注文後品切れや価格変動でキャンセルされる場合がございますので予めご了承願います。 ・当店でご購入された商品は、原則として、「個...

    • Introduction to Deep Learning Business Applications for Developers From Conversational Bots in Customer Service to Medical Image Processing【電子書籍】[ Armando Vieira ]

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  • ＜p＞Discover the potential applications, challenges, and opportunities of deep learning from a business perspective with technical examples. These applications include image recognition, segmentation and annotation, video processing and annotation, voice recognition, intelligent personal assistants, automated translation, and autonomous vehicles.＜/p＞ ＜p＞＜em＞An Introduction to Deep Learning Business Applications for Developers＜/em＞ covers some common DL algorithms such as content-based recommendation algorithms and natural language processing. You’ll explore examples, such as video prediction with fully convolutional neural networks (FCNN) and residual neural networks (ResNets). You will also see applications of DL for controlling robotics, exploring the DeepQ learning algorithm with Monte Carlo Tree search (used to beat humans in the game of Go), and modeling for financial risk assessment. There will also be mention of the powerful set of algorithms called Generative Advers...

    • 【中古】【輸入品・未使用】Introduction to Deep Learning: From Logical Calculus to Artificial Intelligence (Undergraduate Topics in Computer Science)

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  • 【中古】【輸入品・未使用】Introduction to Deep Learning: From Logical Calculus to Artificial Intelligence (Undergraduate Topics in Computer Science)【メーカー名】Springer【メーカー型番】【ブランド名】Springer【商品説明】Introduction to Deep Learning: From Logical Calculus to Artificial Intelligence (Undergraduate Topics in Computer Science)当店では初期不良に限り、商品到着から7日間は返品を 受付けております。こちらは海外販売用に買取り致しました未使用品です。買取り致しました為、中古扱いとしております。他モールとの併売品の為、完売の際はご連絡致しますのでご了承下さい。速やかにご返金させて頂きます。ご注文からお届けまで1、ご注文⇒ご注文は24時間受け付けております。2、注文確認⇒ご注文後、当店から注文確認メールを送信します。3、配送⇒当店海外倉庫から取り寄せの場合は10〜30日程度でのお届けとなります。国内到着後、発送の際に通知にてご連絡致します。国内倉庫からの場合は3〜7日でのお届けとなります。　※離島、北海道、九州、沖縄は遅れる場合がございます。予めご了承下さい。お電話でのお問合せは少人数で運営の為...

    • Introduction to Deep Learning【電子書籍】[ Eugene Charniak ]

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  • ＜p＞＜strong＞A project-based guide to the basics of deep learning.＜/strong＞＜/p＞ ＜p＞This concise, project-driven guide to deep learning takes readers through a series of program-writing tasks that introduce them to the use of deep learning in such areas of artificial intelligence as computer vision, natural-language processing, and reinforcement learning. The author, a longtime artificial intelligence researcher specializing in natural-language processing, covers feed-forward neural nets, convolutional neural nets, word embeddings, recurrent neural nets, sequence-to-sequence learning, deep reinforcement learning, unsupervised models, and other fundamental concepts and techniques. Students and practitioners learn the basics of deep learning by working through programs in Tensorflow, an open-source machine learning framework. “I find I learn computer science material best by sitting down and writing programs,” the author writes, and the book reflects this approach.＜/p＞ ＜p＞E...

    • Introduction to Deep Learning Using R A Step-by-Step Guide to Learning and Implementing Deep Learning Models Using R【電子書籍】[ Taweh Beysolow II ]

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  • ＜p＞Understand deep learning, the nuances of its different models, and where these models can be applied.＜/p＞ ＜p＞The abundance of data and demand for superior products/services have driven the development of advanced computer science techniques, among them image and speech recognition. ＜em＞Introduction to Deep Learning Using R＜/em＞ provides a theoretical and practical understanding of the models that perform these tasks by building upon the fundamentals of data science through machine learning and deep learning. This step-by-step guide will help you understand the disciplines so that you can apply the methodology in a variety of contexts. All examples are taught in the R statistical language, allowing students and professionals to implement these techniques using open source tools.＜/p＞ ＜p＞＜strong＞What You'll Learn＜/strong＞＜/p＞ ＜ul＞ ＜li＞ ＜p＞Understand the intuition and mathematics that power deep learning models＜/p＞ ＜/li＞ ＜li＞ ＜p＞Utilize various algor...
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