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Deep learning with Python [2nd ed.] / François Chollet (2021, cop. 2023)

Public ISBD Titre : Deep learning with Python [2nd ed.] Type de document : texte imprimé Auteurs : François Chollet (1989-....), Auteur Mention d'édition : Second Edition Editeur : Shelter Island, NY : Manning publications Année de publication : 2021, cop. 2023 Importance : 1 vol. (XXIV-478 p.) Présentation : ill. en noir et coul., couv. ill. en coul., phot. Format : 24 cm ISBN/ISSN/EAN : 978-1-61729-686-4 Note générale : ISBN : 1-61729-686-4 .- PPN 261543172 EAN : 9781617296864 Langues : Anglais (eng) Tags : Python (langage de programmation)  Apprentissage automatique  Apprentissage profond  Réseaux neuronaux (informatique)  Python (Computer program language)  Machine learning  Neural networks (Computer science) Index. décimale : 005.133 Langages de programmation particuliers Résumé : En 4e de couverture : "Recent innovations in deep learning unlock exciting new software capabilities like automated language translation, image recognition, and more. Deep learning is quickly becoming essential knowledge for every software developer, and modern tools like Keras and TensorFlow put it within your reach-- even if you have no background in mathematics or data science. This book shows you how to get started. "Deep learning with Python, second edition" introduces the field of deep learning using Python and the powerful Keras library. In this revised and expanded new edition, Keras creator François Chollet offers insights for both novice and experienced machine learning practitioners. As you move through this book, you'll build your understanding through intuitive explanations, crisp illustrations, and clear examples. You'll quickly pick up the skills you need to start developing deep-learning applications." Note de contenu : Index Sommaire : 1. What is deep learning?.2. The mathematical building blocks of neural networks.3. Introduction to Keras and TensorFlow.4. Getting started with neural networks: classification and regression.5. Fundamentals of machine learning.6. The universal workflow of machine learning.7. Working with Keras: a deep dive.8. Introduction to deep learning for computer vision.9. Advanced deep learning for computer vision.10. Deep learning for timeseries.11. Deep learning for text.12. Generative deep learning.13. Best practices for the real world.14. Conclusions Deep learning with Python [2nd ed.] [texte imprimé] / François Chollet (1989-....), Auteur  . -  Second Edition . - Shelter Island, NY : Manning publications, 2021, cop. 2023 . - 1 vol. (XXIV-478 p.) : ill. en noir et coul., couv. ill. en coul., phot. ; 24 cm. ISBN : 978-1-61729-686-4 ISBN : 1-61729-686-4 .- PPN 261543172 EAN : 9781617296864 Langues : Anglais (eng) Tags : Python (langage de programmation)  Apprentissage automatique  Apprentissage profond  Réseaux neuronaux (informatique)  Python (Computer program language)  Machine learning  Neural networks (Computer science) Index. décimale : 005.133 Langages de programmation particuliers Résumé : En 4e de couverture : "Recent innovations in deep learning unlock exciting new software capabilities like automated language translation, image recognition, and more. Deep learning is quickly becoming essential knowledge for every software developer, and modern tools like Keras and TensorFlow put it within your reach-- even if you have no background in mathematics or data science. This book shows you how to get started. "Deep learning with Python, second edition" introduces the field of deep learning using Python and the powerful Keras library. In this revised and expanded new edition, Keras creator François Chollet offers insights for both novice and experienced machine learning practitioners. As you move through this book, you'll build your understanding through intuitive explanations, crisp illustrations, and clear examples. You'll quickly pick up the skills you need to start developing deep-learning applications." Note de contenu : Index Sommaire : 1. What is deep learning?.2. The mathematical building blocks of neural networks.3. Introduction to Keras and TensorFlow.4. Getting started with neural networks: classification and regression.5. Fundamentals of machine learning.6. The universal workflow of machine learning.7. Working with Keras: a deep dive.8. Introduction to deep learning for computer vision.9. Advanced deep learning for computer vision.10. Deep learning for timeseries.11. Deep learning for text.12. Generative deep learning.13. Best practices for the real world.14. Conclusions

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Modern Fortran / Milan Curcic (2021)

Public ISBD Titre : Modern Fortran : building efficient parallel applications Type de document : texte imprimé Auteurs : Milan Curcic, Auteur ; Damian Rouson, Préfacier, etc. Editeur : Shelter Island, NY : Manning publications Année de publication : 2021 Importance : 1 vol. (xxiii-389 p.) Présentation : ill. Format : 24 cm ISBN/ISSN/EAN : 978-1-61729-528-7 Note générale : PPN 25680141X .- Contient : Part 1. Getting started with modern Fortran. Introducing Fortran. - Getting started : minimal working app. - Part 2. Core elements of Fortran. Writing reusable code with functions and subroutines. - Organizing your Fortran code using modules. - Analyzing time series data with arrays. - Reading, writing, and formatting your data. - Part 3. Advanced Fortran use. Going parallel with Fortran coarrays. - Working with abstract data using derived types. - Generic procedures and operators for any data type. - User-defined operators for derived types. - Part 4. The final stretch. Interoperability with C: exposing your app to the web. - Advanced parallelism with teams, events, and collectivesContient : Part 1. Getting started with modern Fortran. Introducing Fortran. - Getting started : minimal working app. - Part 2. Core elements of Fortran. Writing reusable code with functions and subroutines. - Organizing your Fortran code using modules. - Analyzing time series data with arrays. - Reading, writing, and formatting your data. - Part 3. Advanced Fortran use. Going parallel with Fortran coarrays. - Working with abstract data using derived types. - Generic procedures and operators for any data type. - User-defined operators for derived types. - Part 4. The final stretch. Interoperability with C: exposing your app to the web. - Advanced parallelism with teams, events, and collectives Langues : Anglais (eng) Tags : Fortran (langage de programmation) -- Guides, manuels, etc.  Langages de programmation -- Guides, manuels, etc.  FORTRAN (Computer program language) -- Handbooks, manuals, etc.  Programming languages (Electronic computers) -- Handbooks, manuals, etc. Index. décimale : 005.133 Langages de programmation particuliers Résumé : "Modern Fortran teaches you to develop fast, efficient parallel applications using twenty-first-century Fortran. In this guide, you'll dive into Fortran by creating fun apps, including a tsunami simulator and a stock price analyzer. Filled with real-world use cases, insightful illustrations, and hands-on exercises, Modern Fortran helps you see this classic language in a whole new light.(source : 4ème de couverture) Note de contenu : Références bibliographiques et exercices en fin de chapitre - Index : p.381-389 Modern Fortran : building efficient parallel applications [texte imprimé] / Milan Curcic, Auteur ; Damian Rouson, Préfacier, etc. . - Shelter Island, NY : Manning publications, 2021 . - 1 vol. (xxiii-389 p.) : ill. ; 24 cm. ISBN : 978-1-61729-528-7 PPN 25680141X .- Contient : Part 1. Getting started with modern Fortran. Introducing Fortran. - Getting started : minimal working app. - Part 2. Core elements of Fortran. Writing reusable code with functions and subroutines. - Organizing your Fortran code using modules. - Analyzing time series data with arrays. - Reading, writing, and formatting your data. - Part 3. Advanced Fortran use. Going parallel with Fortran coarrays. - Working with abstract data using derived types. - Generic procedures and operators for any data type. - User-defined operators for derived types. - Part 4. The final stretch. Interoperability with C: exposing your app to the web. - Advanced parallelism with teams, events, and collectivesContient : Part 1. Getting started with modern Fortran. Introducing Fortran. - Getting started : minimal working app. - Part 2. Core elements of Fortran. Writing reusable code with functions and subroutines. - Organizing your Fortran code using modules. - Analyzing time series data with arrays. - Reading, writing, and formatting your data. - Part 3. Advanced Fortran use. Going parallel with Fortran coarrays. - Working with abstract data using derived types. - Generic procedures and operators for any data type. - User-defined operators for derived types. - Part 4. The final stretch. Interoperability with C: exposing your app to the web. - Advanced parallelism with teams, events, and collectives Langues : Anglais (eng) Tags : Fortran (langage de programmation) -- Guides, manuels, etc.  Langages de programmation -- Guides, manuels, etc.  FORTRAN (Computer program language) -- Handbooks, manuals, etc.  Programming languages (Electronic computers) -- Handbooks, manuals, etc. Index. décimale : 005.133 Langages de programmation particuliers Résumé : "Modern Fortran teaches you to develop fast, efficient parallel applications using twenty-first-century Fortran. In this guide, you'll dive into Fortran by creating fun apps, including a tsunami simulator and a stock price analyzer. Filled with real-world use cases, insightful illustrations, and hands-on exercises, Modern Fortran helps you see this classic language in a whole new light.(source : 4ème de couverture) Note de contenu : Références bibliographiques et exercices en fin de chapitre - Index : p.381-389

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