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Basi6 International, Irving, TX, Estados Unidos de America
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Vendedor de AbeBooks desde 24 de junio de 2016
New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service. N° de ref. del artículo ABEJUNE24-11664
This fully revised second edition of Machine Learning with TensorFlow teaches you the foundational concepts of machine learning and how to utilize the TensorFlow library to rapidly build powerful ML models. You’ll learn the basics of regression, classification, and clustering algorithms, applying them to solve real-world challenges.
New and revised content expands coverage of core machine learning algorithms and advancements in neural networks such as VGG-Face facial identification classifiers and deep speech classifiers. Written by NASA JPL Deputy CTO and Principal Data Scientist Chris Mattmann, all examples are accompanied by downloadable Jupyter Notebooks for a hands-on experience coding TensorFlow with Python.
Key Features
· Visualizing algorithms with TensorBoard
· Understanding and using neural networks
· Reproducing and employing predictive science
· Downloadable Jupyter Notebooks for all examples
· Questions to test your knowledge
· Examples use the super-stable 1.14.1 branch of TensorFlow
Developers experienced with Python and algebraic concepts like
vectors and matrices.
About the technology
TensorFlow, Google’s library for large-scale machine learning, makes powerful ML techniques easily accessible. It simplifies often-complex computations by representing them as graphs that are mapped to machines in a cluster or to the processors of a single machine. Offering a complete ecosystem for all stages and types of machine learning, TensorFlow’s end-to-end functionality empowers machine learning engineers of all skill levels to solve their problems with ML.
Chris Mattmann is the Deputy Chief Technology and Innovation Officer at NASA Jet Propulsion Lab, where he has been recognised as JPL's first Principal Scientist in the area of Data Science. Chris has applied TensorFlow to challenges he’s faced at NASA, including building an implementation of Google’s Show & Tell algorithm for image captioning using TensorFlow. He contributes to open source as a former Director at the Apache Software Foundation, and teaches graduate courses at USC in
Content Detection and Analysis, and in Search Engines and Information Retrieval.
Nishant Shukla wrote the first edition of Machine Learning with TensorFlow.
Acerca del autor:
Chris Mattmann is the Deputy Chief Technology and Innovation Officer at NASA Jet Propulsion Lab, where he has been recognised as JPL's first Principal Scientist in the area of Data Science. Chris has applied TensorFlow to challenges he’s faced at NASA, including building an implementation of Google’s Show & Tell algorithm for image captioning using TensorFlow. He contributes to open source as a former Director at the Apache Software Foundation, and teaches graduate courses at USC in
Content Detection and Analysis, and in Search Engines and Information Retrieval.
Nishant Shukla wrote the first edition of Machine Learning with TensorFlow.
Título: Machine Learning with TensorFlow (Book)
Editorial: Manning
Año de publicación: 2021
Encuadernación: Encuadernación de tapa blanda
Condición: Brand New
Edición: 2ª Edición
Librería: HPB-Red, Dallas, TX, Estados Unidos de America
Paperback. Condición: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority! Nº de ref. del artículo: S_408005501
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Librería: clickgoodwillbooks, Indianapolis, IN, Estados Unidos de America
Condición: acceptable. Used - Acceptable: All pages and the cover are intact, but shrink wrap, dust covers, or boxed set case may be missing. Pages may include limited notes, highlighting, or minor water damage but the text is readable. Item may be missing bundled media. Nº de ref. del artículo: 3O6WBH0013YF_ns
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Librería: BooksRun, Philadelphia, PA, Estados Unidos de America
Paperback. Condición: Good. 2nd ed. It's a preowned item in good condition and includes all the pages. It may have some general signs of wear and tear, such as markings, highlighting, slight damage to the cover, minimal wear to the binding, etc., but they will not affect the overall reading experience. Nº de ref. del artículo: 1617297712-11-1
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Condición: As New. Unread copy in mint condition. Nº de ref. del artículo: SS9781617297717
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Condición: New. Brand New. Nº de ref. del artículo: 9781617297717
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Librería: Majestic Books, Hounslow, Reino Unido
Condición: New. pp. 350. Nº de ref. del artículo: 380401655
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Librería: Rarewaves USA, OSWEGO, IL, Estados Unidos de America
Paperback. Condición: New. This fully revised second edition of Machine Learning with TensorFlow teaches you the foundational concepts of machine learning and how to utilize the TensorFlow library to rapidly build powerful ML models. You'll learn the basics of regression, classification, and clustering algorithms, applying them to solve real-world challenges. New and revised content expands coverage of core machine learning algorithms and advancements in neural networks such as VGG-Face facial identification classifiers and deep speech classifiers. Written by NASA JPL Deputy CTO and Principal Data Scientist Chris Mattmann, all examples are accompanied by downloadable Jupyter Notebooks for a hands-on experience coding TensorFlow with Python. Key Features · Visualizing algorithms with TensorBoard · Understanding and using neural networks · Reproducing and employing predictive science · Downloadable Jupyter Notebooks for all examples · Questions to test your knowledge · Examples use the super-stable 1.14.1 branch of TensorFlow Developers experienced with Python and algebraic concepts like vectors and matrices. About the technology TensorFlow, Google's library for large-scale machine learning, makes powerful ML techniques easily accessible. It simplifies often-complex computations by representing them as graphs that are mapped to machines in a cluster or to the processors of a single machine. Offering a complete ecosystem for all stages and types of machine learning, TensorFlow's end-to-end functionality empowers machine learning engineers of all skill levels to solve their problems with ML. Chris Mattmann is the Deputy Chief Technology and Innovation Officer at NASA Jet Propulsion Lab, where he has been recognised as JPL's first Principal Scientist in the area of Data Science. Chris has applied TensorFlow to challenges he's faced at NASA, including building an implementation of Google's Show and Tell algorithm for image captioning using TensorFlow. He contributes to open source as a former Director at the Apache Software Foundation, and teaches graduate courses at USC in Content Detection and Analysis, and in Search Engines and Information Retrieval. Nishant Shukla wrote the first edition of Machine Learning with TensorFlow. Nº de ref. del artículo: LU-9781617297717
Cantidad disponible: 10 disponibles
Librería: Books Puddle, New York, NY, Estados Unidos de America
Condición: New. pp. 350. Nº de ref. del artículo: 26383502376
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Librería: Biblios, Frankfurt am main, HESSE, Alemania
Condición: New. pp. 350. Nº de ref. del artículo: 18383502370
Cantidad disponible: 4 disponibles
Librería: Rarewaves USA United, OSWEGO, IL, Estados Unidos de America
Paperback. Condición: New. This fully revised second edition of Machine Learning with TensorFlow teaches you the foundational concepts of machine learning and how to utilize the TensorFlow library to rapidly build powerful ML models. You'll learn the basics of regression, classification, and clustering algorithms, applying them to solve real-world challenges. New and revised content expands coverage of core machine learning algorithms and advancements in neural networks such as VGG-Face facial identification classifiers and deep speech classifiers. Written by NASA JPL Deputy CTO and Principal Data Scientist Chris Mattmann, all examples are accompanied by downloadable Jupyter Notebooks for a hands-on experience coding TensorFlow with Python. Key Features · Visualizing algorithms with TensorBoard · Understanding and using neural networks · Reproducing and employing predictive science · Downloadable Jupyter Notebooks for all examples · Questions to test your knowledge · Examples use the super-stable 1.14.1 branch of TensorFlow Developers experienced with Python and algebraic concepts like vectors and matrices. About the technology TensorFlow, Google's library for large-scale machine learning, makes powerful ML techniques easily accessible. It simplifies often-complex computations by representing them as graphs that are mapped to machines in a cluster or to the processors of a single machine. Offering a complete ecosystem for all stages and types of machine learning, TensorFlow's end-to-end functionality empowers machine learning engineers of all skill levels to solve their problems with ML. Chris Mattmann is the Deputy Chief Technology and Innovation Officer at NASA Jet Propulsion Lab, where he has been recognised as JPL's first Principal Scientist in the area of Data Science. Chris has applied TensorFlow to challenges he's faced at NASA, including building an implementation of Google's Show and Tell algorithm for image captioning using TensorFlow. He contributes to open source as a former Director at the Apache Software Foundation, and teaches graduate courses at USC in Content Detection and Analysis, and in Search Engines and Information Retrieval. Nishant Shukla wrote the first edition of Machine Learning with TensorFlow. Nº de ref. del artículo: LU-9781617297717
Cantidad disponible: 10 disponibles