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As part of the best-selling Pocket Primer series, this book is designed to introduce beginners to basic machine learning algorithms using TensorFlow 2. It is intended to be a fast-paced introduction to various core features of TensorFlow, with code samples that cover machine learning and TensorFlow basics. A comprehensive appendix contains some Keras-based code samples and the underpinnings of MLPs, CNNs, RNNs, and LSTMs. The material in the chapters illustrates how to solve a variety of tasks after which you can do further reading to deepen your knowledge. Companion files with all of the code samples are available for downloading from the publisher by emailing proof of purchase to info@merclearning.com. Features: Uses Python for code samples Covers TensorFlow 2 APIs and Datasets Includes a comprehensive appendix that covers Keras and advanced topics such as NLPs, MLPs, RNNs, LSTMs Features the companion files with all of the source code examples and figures (download from the publisher)
Über die Autorin bzw. den Autor: Oswald Campesato specializes in Deep Learning, Python, Data Science, and generative AI. He is the author/co-author of over forty books including Google Gemini for Python, Data Cleaning, and GPT-4 for Developers (all Mercury Learning).
Titel: TensorFlow 2 Pocket Primer (Computing)
Verlag: Mercury Learning & Information
Erscheinungsdatum: 2019
Einband: Paperback
Zustand: Very Good
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Paperback. Zustand: new. Paperback. As part of the best-selling Pocket Primer series, this book is designed to introduce beginners to basic machine learning algorithms using TensorFlow 2. It is intended to be a fast-paced introduction to various core features of TensorFlow, with code samples that cover machine learning and TensorFlow basics. A comprehensive appendix contains some Keras-based code samples and the underpinnings of MLPs, CNNs, RNNs, and LSTMs. The material in the chapters illustrates how to solve a variety of tasks after which you can do further reading to deepen your knowledge. Companion files with all of the code samples are available for downloading from the publisher by emailing proof of purchase to . Features: Uses Python for code samplesCovers TensorFlow 2 APIs and DatasetsIncludes a comprehensive appendix that covers Keras and advanced topics such as NLPs, MLPs, RNNs, LSTMsFeatures the companion files with all of the source code examples and figures (download from the publisher) Introduces beginners to basic machine learning algorithms using TensorFlow 2. The book is intended to be a fast-paced introduction to various ""core"" features of TensorFlow, with code samples that cover machine learning and TensorFlow basics. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Bestandsnummer des Verkäufers 9781683924609
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Paperback. Zustand: new. Paperback. As part of the best-selling Pocket Primer series, this book is designed to introduce beginners to basic machine learning algorithms using TensorFlow 2. It is intended to be a fast-paced introduction to various core features of TensorFlow, with code samples that cover machine learning and TensorFlow basics. A comprehensive appendix contains some Keras-based code samples and the underpinnings of MLPs, CNNs, RNNs, and LSTMs. The material in the chapters illustrates how to solve a variety of tasks after which you can do further reading to deepen your knowledge. Companion files with all of the code samples are available for downloading from the publisher by emailing proof of purchase to . Features: Uses Python for code samplesCovers TensorFlow 2 APIs and DatasetsIncludes a comprehensive appendix that covers Keras and advanced topics such as NLPs, MLPs, RNNs, LSTMsFeatures the companion files with all of the source code examples and figures (download from the publisher) Introduces beginners to basic machine learning algorithms using TensorFlow 2. The book is intended to be a fast-paced introduction to various ""core"" features of TensorFlow, with code samples that cover machine learning and TensorFlow basics. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Bestandsnummer des Verkäufers 9781683924609
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Campesato Oswald : Oswald Campesato (San Francisco, CA) is an adjunct instructor at UC-Santa Clara and specializes in Deep Learning, Java, Android, TensorFlow, and NLP. He is the author/co-author of over twenty-five books including TensorFlow 2 Po. Bestandsnummer des Verkäufers 302610045
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Taschenbuch. Zustand: Neu. Neuware 250 pp. Englisch. Bestandsnummer des Verkäufers 9781683924609
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 250 pp. Englisch. Bestandsnummer des Verkäufers 9781683924609
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering. Bestandsnummer des Verkäufers 9781683924609
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