Mattmann chris (37 résultats)

Paperback. Etat : Fair. 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.…

Paperback. Etat : Good. 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.…

Paperback. Etat : Good. "Tika in Action" is a hands-on guide for developers working with search engines, content management systems, and other similar applications who want to exploit the information locked in digital documents. It introduces the world of mining text and binary documents as well as other information sources.…

Paperback. Etat : Very Good. "Tika in Action" is a hands-on guide for developers working with search engines, content management systems, and other similar applications who want to exploit the information locked in digital documents. It introduces the world of mining text and binary documents as well as other information sources.…

Paperback. Etat : Very Good. First Edition. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.

Paperback. Etat : Fair. 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.…

Paperback. Etat : Good. 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.…

Paperback. Etat : Very Good. 2nd ed. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.

Etat : Good. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Paperback. Etat : Very Good. 2nd ed. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.

Etat : Good. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Etat : Very Good. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Etat : 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.

Paperback. Etat : Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.

Paperback. Etat : Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.

Paperback. Etat : Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.

Paperback. Etat : Very Good. "Tika in Action" is a hands-on guide for developers working with search engines, content management systems, and other similar applications who want to exploit the information locked in digital documents. It introduces the world of mining text and binary documents as well as other information sources.…

Paperback. Etat : Good. "Tika in Action" is a hands-on guide for developers working with search engines, content management systems, and other similar applications who want to exploit the information locked in digital documents. It introduces the world of mining text and binary documents as well as other information sources.…

Paperback. Etat : 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.

Paperback. Etat : 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.

Paperback. Etat : Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.

Paperback. Etat : Good. Book in Good condition.

paperback. Etat : Very Good. Connecting readers with great books since 1972! Used books may not include companion materials, and may have some shelf wear or limited writing. We ship orders daily and Customer Service is our top priority.

Paperback. Etat : new. New Copy. Customer Service Guaranteed.

Etat : new.

Etat : As New. Unread copy in mint condition.

Etat : New. Brand New.

Paperback. Etat : 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.…

Etat : very good. Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages.

Etat : New. pp. 350.