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Reactive Publishing, 2024. — 654 p. In an era where Artificial Intelligence is revolutionizing industries, mastering the tools and techniques to harness its potential is essential. Mastering Keras: Building Advanced Deep Learning Models with Python is your comprehensive guide to diving deep into the world of neural networks and Deep Learning using Keras, one of the most...
  • 3,03 МБ
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Reactive Publishing, 2024. — 654 p. In an era where Artificial Intelligence is revolutionizing industries, mastering the tools and techniques to harness its potential is essential. Mastering Keras: Building Advanced Deep Learning Models with Python is your comprehensive guide to diving deep into the world of neural networks and Deep Learning using Keras, one of the most...
  • 2,87 МБ
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Reactive Publishing, 2024. — 654 p. In an era where Artificial Intelligence is revolutionizing industries, mastering the tools and techniques to harness its potential is essential. Mastering Keras: Building Advanced Deep Learning Models with Python is your comprehensive guide to diving deep into the world of neural networks and Deep Learning using Keras, one of the most...
  • 3,93 МБ
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3e édition. — Dunod, 2024. — 626 p. — ISBN 9782100847693. L’objectif de cet ouvrage est de vous expliquer les concepts fondamentaux du Deep Learning et de vous montrer, grâce à de nombreux exemples de code accessibles en ligne, comment les mettre en pratique. La 3e édition de cet ouvrage de référence, très remaniée, tient compte des récentes avancées. - Construire et entraîner...
  • 16,85 МБ
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Elektor Publication, 2022. — 248 p. Most people are increasingly confronted with the applications of Artificial Intelligence (AI). Music or video ratings, navigation systems, shopping advice, etc. are based on methods that can be attributed to this field. The term Artificial Intelligence was coined in 1956 at an international conference known as the Dartmouth Summer Research...
  • 4,07 МБ
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Independently published, 2021. — 68 p. — ASIN : B0947GKFSZ. This book will introduce you to various supervised and unsupervised deep learning algorithms like the multilayer perceptron, linear regression, and other more advanced deep convolutional and recurrent neural networks. You will also learn about image processing, handwritten recognition, object recognition, and much...
  • 897,23 КБ
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Independently published, 2021. — 68 p. — ASIN : B0947GKFSZ. This book will introduce you to various supervised and unsupervised deep learning algorithms like the multilayer perceptron, linear regression, and other more advanced deep convolutional and recurrent neural networks. You will also learn about image processing, handwritten recognition, object recognition, and much...
  • 5,09 МБ
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Independently published, 2021. — 68 p. — ASIN : B0947GKFSZ. This book will introduce you to various supervised and unsupervised deep learning algorithms like the multilayer perceptron, linear regression, and other more advanced deep convolutional and recurrent neural networks. You will also learn about image processing, handwritten recognition, object recognition, and much...
  • 699,59 КБ
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Apress, 2019. — 182 p. — ISBN13: (electronic): 978-1-4842-4240-7. Learn, understand, and implement deep neural networks in a math- and programming-friendly approach using Keras and Python. The book focuses on an end-to-end approach to developing supervised learning algorithms in regression and classification with practical business-centric use-cases implemented in Keras. The...
  • 2,19 МБ
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Apress, 2019. — 182 p. — ISBN13: (electronic): 978-1-4842-4240-7. Learn, understand, and implement deep neural networks in a math- and programming-friendly approach using Keras and Python. The book focuses on an end-to-end approach to developing supervised learning algorithms in regression and classification with practical business-centric use-cases implemented in Keras. The...
  • 2,19 МБ
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Apress, 2019. — 182 p. — ISBN13: 978-1-4842-4239-1. Learn, understand, and implement deep neural networks in a math- and programming-friendly approach using Keras and Python. The book focuses on an end-to-end approach to developing supervised learning algorithms in regression and classification with practical business-centric use-cases implemented in Keras. The overall book...
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Wiley, 2019. — 313 p. — ISBN: 978-1-119-56486-7. Build a Keras model to scale and deploy on a Kubernetes cluster We have seen an exponential growth in the use of Artificial Intelligence (AI) over last few years. AI is becoming the new electricity and is touching every industry from retail to manufacturing to healthcare to entertainment. Within AI, we’re seeing a particular...
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Packt, 2018. — 288 p. Reinforcement learning has evolved a lot in the last couple of years and proven to be a successful technique in building smart and intelligent AI networks. Keras Reinforcement Learning Projects installs human-level performance into your applications using algorithms and techniques of reinforcement learning, coupled with Keras, a faster experimental library....
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Packt Publishing, 2018. — 368 p. — ASIN B078N8RDCP. A comprehensive guide to advanced deep learning techniques, including Autoencoders, GANs, VAEs, and Deep Reinforcement Learning, that drive today's most impressive AI results Key Features Explore the most advanced deep learning techniques that drive modern AI results Implement Deep Neural Networks, Autoencoders, GANs, VAEs,...
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Packt Publishing, 2018. — 368 p. — ASIN B078N8RDCP. !Code files only. A comprehensive guide to advanced deep learning techniques, including Autoencoders, GANs, VAEs, and Deep Reinforcement Learning, that drive today's most impressive AI results Key Features Explore the most advanced deep learning techniques that drive modern AI results Implement Deep Neural Networks,...
  • 123,16 МБ
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Packt Publishing, 2018. — 368 p. — ASIN B078N8RDCP. A comprehensive guide to advanced deep learning techniques, including Autoencoders, GANs, VAEs, and Deep Reinforcement Learning, that drive today's most impressive AI results Key Features Explore the most advanced deep learning techniques that drive modern AI results Implement Deep Neural Networks, Autoencoders, GANs, VAEs,...
  • 15,61 МБ
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Packt Publishing, 2018. — 368 p. — ASIN B078N8RDCP. A comprehensive guide to advanced deep learning techniques, including Autoencoders, GANs, VAEs, and Deep Reinforcement Learning, that drive today's most impressive AI results Key Features Explore the most advanced deep learning techniques that drive modern AI results Implement Deep Neural Networks, Autoencoders, GANs, VAEs,...
  • 15,20 МБ
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Apress, 2019. — 182 p. Learn, understand, and implement deep neural networks in a math- and programming-friendly approach using Keras and Python. The book focuses on an end-to-end approach to developing supervised learning algorithms in regression and classification with practical business-centric use-cases implemented in Keras. The overall book comprises three sections with...
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Apress, 2019. — 182 p. Learn, understand, and implement deep neural networks in a math- and programming-friendly approach using Keras and Python. The book focuses on an end-to-end approach to developing supervised learning algorithms in regression and classification with practical business-centric use-cases implemented in Keras. The overall book comprises three sections with...
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Amazon Digital Services LLC, 2018. — 189 р. This introduction will help you develop a good understanding of deep learning completely from scratch This book covers: Introduction to machine learning and deep learning Math for deep learning explained to the layman How neural networks work: a general overview Activation functions in deep networks Loss functions Weight...
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Amazon Digital Services LLC, 2018. — 189 р. This introduction will help you develop a good understanding of deep learning completely from scratch This book covers: Introduction to machine learning and deep learning Math for deep learning explained to the layman How neural networks work: a general overview Activation functions in deep networks Loss functions Weight...
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Amazon Digital Services LLC, 2018. — 189 р. This introduction will help you develop a good understanding of deep learning completely from scratch This book covers: Introduction to machine learning and deep learning Math for deep learning explained to the layman How neural networks work: a general overview Activation functions in deep networks Loss functions Weight...
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Packt Publishing, 2017. — 318 p. — ISBN: 978-1-78712-842-2. Get to grips with the basics of Keras to implement fast and efficient deep-learning models This book starts by introducing you to supervised learning algorithms such as simple linear regression, the classical multilayer perceptron and more sophisticated deep convolutional networks. You will also explore image...
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Packt Publishing, 2017. — 318 p. — ISBN: 978-1-78712-842-2. True PDF Get to grips with the basics of Keras to implement fast and efficient deep-learning models This book starts by introducing you to supervised learning algorithms such as simple linear regression, the classical multilayer perceptron and more sophisticated deep convolutional networks. You will also explore image...
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