{"product_id":"deep-learning-with-python","title":"Deep Learning with Python","description":"Summary\n\nDeep 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 François Chollet, this book builds your understanding through intuitive explanations and practical examples.\n\nPurchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.\n\nAbout the Technology\n\nMachine learning has made remarkable progress in recent years. We went from near-unusable speech and image recognition, to near-human accuracy. We went from machines that couldn't beat a serious Go player, to defeating a world champion. Behind this progress is deep learning—a combination of engineering advances, best practices, and theory that enables a wealth of previously impossible smart applications.\n\nAbout the Book\n\nDeep 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 François Chollet, this book builds your understanding through intuitive explanations and practical examples. You'll explore challenging concepts and practice with applications in computer vision, natural-language processing, and generative models. By the time you finish, you'll have the knowledge and hands-on skills to apply deep learning in your own projects.\n\nWhat's Inside\nDeep learning from first principles Setting up your own deep-learning environment Image-classification models Deep learning for text and sequences Neural style transfer, text generation, and image generation\nAbout the Reader\n\nReaders need intermediate Python skills. No previous experience with Keras, Tensor Flow, or machine learning is required.\n\nAbout the Author\n\nFrançois Chollet works on deep learning at Google in Mountain View, CA. He is the creator of the Keras deep-learning library, as well as a contributor to the Tensor Flow machine-learning framework. He also does deep-learning research, with a focus on computer vision and the application of machine learning to formal reasoning. His papers have been published at major conferences in the field, including the Conference on Computer Vision and Pattern Recognition (CVPR), the Conference and Workshop on Neural Information Processing Systems (NIPS), the International Conference on Learning Representations (ICLR), and others.\n\nTable of Contents\n\nPART 1 - FUNDAMENTALS OF DEEP LEARNING What is deep learning? Before we begin: the mathematical building blocks of neural networks Getting started with neural networks Fundamentals of machine learning PART 2 - DEEP LEARNING IN PRACTICE Deep learning for computer vision Deep learning for text and sequences Advanced deep-learning best practices Generative deep learning Conclusions appendix A - Installing Keras and its dependencies on Ubuntu appendix B - Running Jupiter notebooks on an EC2 GPU instance.\u003cbr\u003eASIN: 1617294438\u003cbr\u003eVSKU: DBV.1617294438.G\u003cbr\u003eCondition: Good\u003cbr\u003eAuthor\/Artist:Chollet, Francois\u003cbr\u003eBinding: Paperback\u003cbr\u003e\u003cb\u003eNote:\u003c\/b\u003e Any images shown are stock photographs and product may differ from what is shown.  \u003cbr\u003e\u003cb\u003eCondition Notes\u003c\/b\u003e: Gently used with minimal wear on the corners and cover. A few pages may contain light highlighting or writing, but the text remains fully legible. Dust jacket may be missing, and supplemental materials like CDs or codes may not be included. May be ex-library with library markings. Ships promptly!  \u003cbr\u003e","brand":"Dream Books Co.","offers":[{"title":"Default Title","offer_id":41444874846266,"sku":"DBV.1617294438.G","price":6.88,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0555\/6011\/0138\/files\/1617294438-0.jpg?v=1780682289","url":"https:\/\/shop.dreambooksco.com\/products\/deep-learning-with-python","provider":"Dream Books Co.","version":"1.0","type":"link"}