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Book details ●

Author : Francois Chollet

Pages : 350 pages

Publisher : Manning

Language : eng

ISBN-10 : 1617294438

ISBN-13 : 9781617294433

Book Synopsis Deep learning is applicable to a widening range of artificial intelligence problems, such as image classification, speech recognition, text classification, question answering, text-to-speech, and optical character recognition. It is the technology behind photo tagging systems at Facebook and Google, self-driving cars, speech recognition systems on your smartphone, and much more.In particular, Deep learning excels at solving machine perception problems: understanding the content of image data, video data, or sound data. Here's a simple example: say you have a large collection of images, and that you want tags associated with each image, for example, "dog," "cat," etc. Deep learning can allow you to create a system that understands how to map such tags to images, learning only from examples. This system can then be applied to new images, automating the task of photo tagging. A deep learning model only has to be fed examples of a task to start generating useful results on new data. CHAPTER TWO DEEP LEARNING TUTORIALS Deep Learning is a new area of Machine Learning research which has been introduced with the objective of moving Machine Learning closer to one of its original goals Arti�cial Intelligence Summary Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library Written by Keras creator and Google AI researcher Fran 231 ois Chollet this book builds your understanding through intuitive explanations and practical examples Book Description Deep 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 Two of the top numerical platforms in Python that provide the basis for Deep Learning research and development are Theano and TensorFlow Both are very powerful libraries but both can be difficult to use directly for creating deep learning models Python Machine Learning Machine Learning and Deep Learning with Python scikit learn and TensorFlow 2nd Edition Sebastian Raschka Vahid Mirjalili on Amazon com FREE shipping on qualifying offers Key Features Second edition of the bestselling book on Machine Learning A practical approach to key frameworks in data When it comes to learning new technology such as deep learning configuring your development environment tends to be half the battle Different operating systems hardware dependencies and the actual libraries themselves can lead to many headaches before you’re even able to get started studying deep learning EDS Subscriber Vault Download free coding cheatsheets machine learning checklists PDF worksheets resource lists and more Utilize Python Keras with either a TensorFlow or Theano backend and mxnet to build deep learning networks Python Keras and mxnet are all well built tools that when combined create a powerful deep learning development environment that you can use to master deep learning for computer vision and visual recognition Need help with Deep Learning in Python Take my free 2 week email course and discover MLPs CNNs and LSTMs with code Click to sign up now and also get a free PDF Ebook version of the course Greetings Welcome to the data repository for the Deep Learning course by Kirill Eremenko and Hadelin de Ponteves The datasets and other supplementary materials are below Enjoy Part 0 Welcome to the course Section 1 Welcome to the course Meet your instructors Deep Learning A Z Folder Structure Updated 20171021 Part 1

`PDF` Download Deep learning with Python  

Download it on pict page 5 .. Enjoy :))

`PDF` Download Deep learning with Python  

Download it on pict page 5 .. Enjoy :))

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