Deep Learning with R 1st Edition by Francois Chollet (PDF)

Description

SummaryDeep Learning with R introduces the world of deep learning using the powerful Keras library and its R language interface. The book builds your understanding of deep learning through intuitive explanations and practical examples. Continue your journey into the world of deep learning with Deep Learning with R in Motion, a practical, hands-on video course available exclusively at Manning.com (www.manning.com/livevideo/deep-​learning-with-r-in-motion).Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.About the TechnologyMachine learning has made remarkable progress in recent years. Deep-learning systems now enable previously impossible smart applications, revolutionizing image recognition and natural-language processing, and identifying complex patterns in data. The Keras deep-learning library provides data scientists and developers working in R a state-of-the-art toolset for tackling deep-learning tasks.About the BookDeep Learning with R introduces the world of deep learning using the powerful Keras library and its R language interface. Initially written for Python as Deep Learning with Python by Keras creator and Google AI researcher François Chollet and adapted for R by RStudio founder J. J. Allaire, this book builds your understanding of deep learning through intuitive explanations and practical examples. You’ll practice your new skills with R-based applications in computer vision, natural-language processing, and generative models.What’s InsideDeep learning from first principlesSetting up your own deep-learning environmentImage classification and generationDeep learning for text and sequencesAbout the ReaderYou’ll need intermediate R programming skills. No previous experience with machine learning or deep learning is assumed.About the AuthorsFrançois Chollet is a deep-learning researcher at Google and the author of the Keras library.J.J. Allaire is the founder of RStudio and the author of the R interfaces to TensorFlow and Keras.Table of ContentsPART 1 – FUNDAMENTALS OF DEEP LEARNINGWhat is deep learning?Before we begin: the mathematical building blocks of neural networksGetting started with neural networksFundamentals of machine learningPART 2 – DEEP LEARNING IN PRACTICEDeep learning for computer visionDeep learning for text and sequencesAdvanced deep-learning best practicesGenerative deep learningConclusions

User’s Reviews

Editorial Reviews: About the Author Francois Chollet is the author of Keras, one of the most widely used libraries for deep learning in Python. He has been working with deep neural networks since 2012. Francois is currently doing deep learning research at Google. He blogs about deep learning at blog.keras.io.J.J. Allaire is the Founder of RStudio and the creator of the RStudio IDE. J.J. is the author of the R interfaces to TensorFlow and Keras.

Reviews from Amazon users which were colected at the time this book was published on the website:

⭐This is thee book if you want to get started in deep learning with keras in R. It is a great intro to neural networks and how they learn. This book also goes over the syntax, functions, and organization of neural nets in keras. Overall a great book.

⭐It is an awesome book because it explains deep learning for dummies without losing technical accuracy. The bad thing is that in a black and white format, you lose the visuals’ details.

⭐i love buying new books and then not reading them. I read this one and learned so much from it.

⭐Very useful book for start learning Deep learning.

⭐The “look inside” button shows a colorful book, but that isn’t the reality. Also, the paper quality seems poor.

⭐Great book with examples. Took me from zero to expert

⭐In three words- an outstanding book!

⭐Very clear, up to date.

⭐Good background on general machine learning concepts, practical advice on machine learning workflow, really good on developing an intuition for some concepts I have always found a bit slippery (why the need for a validation set as well as a test set). This book is well worth the money for getting a solid understanding of and practical introduction to Deep Learning. I’m not a professional practitioner, or academic expert on, the topics covered by the book, but I can see how professionals as well as amateurs like myself interested in the subject can benefit from this book.

⭐An excellent book on using keras in R; one of the best books on deep learning for beginners. Note that it is a direct translation into R of Chollet’s equally excellent book Deep Learning with Python by Allaire, hence the joint authorship

⭐Great purchase, exactly what I was looking for – a broad coverage of DL concepts with R examples using Keras.

⭐He dudado mucho la calificación de este libro. Tiene aspectos mejorables (en mi opinión), pero en otros es excelente.La parte inicial es una introducción a la biblioteca Keras, basada sobre todo, en el desarrollo de ejemplos y de algunos comentarios complementarios.Los ejemplos están bien desarrollados y proporcionan una buena introducción a Keras y a algunas técnicas de Deep Learning. De todos modos, el tema es muy amplio y, aunque el libro es bastante completo, no puede ser exhaustivo y tampoco explica todas las funciones de Keras.Personalmente, hubiera agradecido algo más de detalle en las explicaciones y mas gráficos. Quizá las expresiones matemáticas hubieran ayudado. Se presupone un conocimiento previo de AI (de forma implícita) que puede no estar al alcance de cualquiera. A veces da la impresión que se limita a dar recetas.También es importante indicar que es muy difícil hacer los ejemplos propuestos en el libro sin disponer de GPU u ordenadores especializados.Los últimos capítulos son mas generales. Excelentes en mi opinión, con una vision de las tendencias y limitaciones del Deep learning. Puede ser que, como ocurre en todos los libros, quede obsoleto en poco tiempo, aunque desde luego merecen la penaEl libro trata bien el tema pero esperaba que fuera menos general y que profundizara mucho más en la temática que abarca. No es un mal libro, pero esperaba mucho más en función de las criticas que tiene el libro. Si quieres algo que vaya mucho más allá os recomiendo que busquéis otro libro.

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