Python deep learning :: exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow /
With the surge in artificial intelligence in applications catering to both business and consumer needs, deep learning is more important than ever for meeting current and future market demands. With this book, you'll explore deep learning, and learn how to put machine learning to use in your pro...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Birmingham, UK :
Packt Publishing,
2019.
|
| Ausgabe: | Second edition. |
| Schlagworte: | |
| Online-Zugang: | DE-862 DE-863 |
| Zusammenfassung: | With the surge in artificial intelligence in applications catering to both business and consumer needs, deep learning is more important than ever for meeting current and future market demands. With this book, you'll explore deep learning, and learn how to put machine learning to use in your projects. This second edition of Python Deep Learning will get you up to speed with deep learning, deep neural networks, and how to train them with high-performance algorithms and popular Python frameworks. You'll uncover different neural network architectures, such as convolutional networks, recurrent neural networks, long short-term memory (LSTM) networks, and capsule networks. You'll also learn how to solve problems in the fields of computer vision, natural language processing (NLP), and speech recognition. You'll study generative model approaches such as variational autoencoders and Generative Adversarial Networks (GANs) to generate images. As you delve into newly evolved areas of reinforcement learning, you'll gain an understanding of state-of-the-art algorithms that are the main components behind popular games Go, Atari, and Dota. By the end of the book, you will be well-versed with the theory of deep learning along with its real-world applications. |
| Beschreibung: | 1 online resource (1 volume) : illustrations |
| ISBN: | 1789349702 9781789349702 |
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| contents | Table of ContentsMachine Learning -- An IntroductionNeural NetworksDeep Learning FundamentalsComputer Vision With Convolutional NetworksAdvanced Computer VisionGenerating images with GANs and Variational AutoencodersRecurrent Neural Networks and Language ModelsReinforcement Learning TheoryDeep Reinforcement Learning for GamesDeep Learning in Autonomous Vehicles. |
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| id | ZDB-4-EBA-on1086398837 |
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| spelling | Vasilev, Ivan, author. Python deep learning : exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow / Ivan Vasilev [and four others]. Second edition. Birmingham, UK : Packt Publishing, 2019. 1 online resource (1 volume) : illustrations text txt rdacontent computer c rdamedia online resource cr rdacarrier Online resource; title from title page (Safari, viewed February 15, 2019). Table of ContentsMachine Learning -- An IntroductionNeural NetworksDeep Learning FundamentalsComputer Vision With Convolutional NetworksAdvanced Computer VisionGenerating images with GANs and Variational AutoencodersRecurrent Neural Networks and Language ModelsReinforcement Learning TheoryDeep Reinforcement Learning for GamesDeep Learning in Autonomous Vehicles. With the surge in artificial intelligence in applications catering to both business and consumer needs, deep learning is more important than ever for meeting current and future market demands. With this book, you'll explore deep learning, and learn how to put machine learning to use in your projects. This second edition of Python Deep Learning will get you up to speed with deep learning, deep neural networks, and how to train them with high-performance algorithms and popular Python frameworks. You'll uncover different neural network architectures, such as convolutional networks, recurrent neural networks, long short-term memory (LSTM) networks, and capsule networks. You'll also learn how to solve problems in the fields of computer vision, natural language processing (NLP), and speech recognition. You'll study generative model approaches such as variational autoencoders and Generative Adversarial Networks (GANs) to generate images. As you delve into newly evolved areas of reinforcement learning, you'll gain an understanding of state-of-the-art algorithms that are the main components behind popular games Go, Atari, and Dota. By the end of the book, you will be well-versed with the theory of deep learning along with its real-world applications. Python (Computer program language) http://id.loc.gov/authorities/subjects/sh96008834 Machine learning. http://id.loc.gov/authorities/subjects/sh85079324 Neural networks (Computer science) http://id.loc.gov/authorities/subjects/sh90001937 Artificial intelligence. http://id.loc.gov/authorities/subjects/sh85008180 Neural Networks, Computer https://id.nlm.nih.gov/mesh/D016571 Artificial Intelligence https://id.nlm.nih.gov/mesh/D001185 Machine Learning https://id.nlm.nih.gov/mesh/D000069550 Python (Langage de programmation) Apprentissage automatique. Réseaux neuronaux (Informatique) Intelligence artificielle. artificial intelligence. aat Artificial intelligence fast Machine learning fast Neural networks (Computer science) fast Python (Computer program language) fast Print version: 1789348463 9781789348460 (OCoLC)1073089207 |
| spellingShingle | Vasilev, Ivan Python deep learning : exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow / Table of ContentsMachine Learning -- An IntroductionNeural NetworksDeep Learning FundamentalsComputer Vision With Convolutional NetworksAdvanced Computer VisionGenerating images with GANs and Variational AutoencodersRecurrent Neural Networks and Language ModelsReinforcement Learning TheoryDeep Reinforcement Learning for GamesDeep Learning in Autonomous Vehicles. Python (Computer program language) http://id.loc.gov/authorities/subjects/sh96008834 Machine learning. http://id.loc.gov/authorities/subjects/sh85079324 Neural networks (Computer science) http://id.loc.gov/authorities/subjects/sh90001937 Artificial intelligence. http://id.loc.gov/authorities/subjects/sh85008180 Neural Networks, Computer https://id.nlm.nih.gov/mesh/D016571 Artificial Intelligence https://id.nlm.nih.gov/mesh/D001185 Machine Learning https://id.nlm.nih.gov/mesh/D000069550 Python (Langage de programmation) Apprentissage automatique. Réseaux neuronaux (Informatique) Intelligence artificielle. artificial intelligence. aat Artificial intelligence fast Machine learning fast Neural networks (Computer science) fast Python (Computer program language) fast |
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| title | Python deep learning : exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow / |
| title_auth | Python deep learning : exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow / |
| title_exact_search | Python deep learning : exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow / |
| title_full | Python deep learning : exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow / Ivan Vasilev [and four others]. |
| title_fullStr | Python deep learning : exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow / Ivan Vasilev [and four others]. |
| title_full_unstemmed | Python deep learning : exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow / Ivan Vasilev [and four others]. |
| title_short | Python deep learning : |
| title_sort | python deep learning exploring deep learning techniques and neural network architectures with pytorch keras and tensorflow |
| title_sub | exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow / |
| topic | Python (Computer program language) http://id.loc.gov/authorities/subjects/sh96008834 Machine learning. http://id.loc.gov/authorities/subjects/sh85079324 Neural networks (Computer science) http://id.loc.gov/authorities/subjects/sh90001937 Artificial intelligence. http://id.loc.gov/authorities/subjects/sh85008180 Neural Networks, Computer https://id.nlm.nih.gov/mesh/D016571 Artificial Intelligence https://id.nlm.nih.gov/mesh/D001185 Machine Learning https://id.nlm.nih.gov/mesh/D000069550 Python (Langage de programmation) Apprentissage automatique. Réseaux neuronaux (Informatique) Intelligence artificielle. artificial intelligence. aat Artificial intelligence fast Machine learning fast Neural networks (Computer science) fast Python (Computer program language) fast |
| topic_facet | Python (Computer program language) Machine learning. Neural networks (Computer science) Artificial intelligence. Neural Networks, Computer Artificial Intelligence Machine Learning Python (Langage de programmation) Apprentissage automatique. Réseaux neuronaux (Informatique) Intelligence artificielle. artificial intelligence. Artificial intelligence Machine learning |
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