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    Deep Learning

Deep Learning

Deep Learning
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      Deep Learning: A Comprehensive Guide provides comprehensive coverage of Deep Learning (DL) and Machine Learning (ML) concepts. DL and ML are the most sought-after domains, requiring a deep understanding – and this book gives no less than that. This book enables the reader to build innovative and useful applications based on ML and DL. Starting with the basics of neural networks, and continuing through the architecture of various types of CNNs, RNNs, LSTM, and more till the end of the book, each and every topic is given the utmost care and shaped professionally and comprehensively.Key Features Includes the smooth transition from ML concepts to DL concepts Line-by-line explanations have been provided for all the coding-based examples Includes a lot of real-time examples and interview questions that will prepare the reader to take up a job in ML/DL right away Even a person with a non-computer-science background can benefit from this book by following the theory, examples, case studies, and code snippets Every chapter starts with the objective and ends with a set of quiz questions to test the reader’s understanding Includes references to the related YouTube videos that provide additional guidanceAI is a domain for everyone. This book is targeted toward everyone irrespective of their field of specialization. Graduates and researchers in deep learning will find this book useful.
      Format: CONTRIBUTORS: Deep Learning EAN: 9781032028859 COUNTRY: United Kingdom PAGES: 290 WEIGHT: HEIGHT: 234 cm
      PUBLISHED BY: Taylor & Francis Ltd DATE PUBLISHED: 2024-10-04 CITY: GENRE: COMPUTERS / Database Administration & Management, COMPUTERS / Data Science / Data Analytics, COMPUTERS / Machine Theory, COMPUTERS / Data Science / Data Visualization, COMPUTERS / Data Science / Machine Learning WIDTH: 156 cm SPINE:

      Book Themes:

      Data capture and analysis, Data mining, Mathematical theory of computation, Machine learning

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      Deep Learning: A Comprehensive Guide provides comprehensive coverage of Deep Learning (DL) and Machine Learning (ML) concepts. DL and ML are the most sought-after domains, requiring a deep understanding – and this book gives no less than that. This book enables the reader to build innovative and useful applications based on ML and DL. Starting with the basics of neural networks, and continuing through the architecture of various types of CNNs, RNNs, LSTM, and more till the end of the book, each and every topic is given the utmost care and shaped professionally and comprehensively.Key Features Includes the smooth transition from ML concepts to DL concepts Line-by-line explanations have been provided for all the coding-based examples Includes a lot of real-time examples and interview questions that will prepare the reader to take up a job in ML/DL right away Even a person with a non-computer-science background can benefit from this book by following the theory, examples, case studies, and code snippets Every chapter starts with the objective and ends with a set of quiz questions to test the reader’s understanding Includes references to the related YouTube videos that provide additional guidanceAI is a domain for everyone. This book is targeted toward everyone irrespective of their field of specialization. Graduates and researchers in deep learning will find this book useful.
      Format: CONTRIBUTORS: Deep Learning EAN: 9781032028859 COUNTRY: United Kingdom PAGES: 290 WEIGHT: HEIGHT: 234 cm
      PUBLISHED BY: Taylor & Francis Ltd DATE PUBLISHED: 2024-10-04 CITY: GENRE: COMPUTERS / Database Administration & Management, COMPUTERS / Data Science / Data Analytics, COMPUTERS / Machine Theory, COMPUTERS / Data Science / Data Visualization, COMPUTERS / Data Science / Machine Learning WIDTH: 156 cm SPINE:

      Book Themes:

      Data capture and analysis, Data mining, Mathematical theory of computation, Machine learning

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      Be the first to write a review
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