{"product_id":"deep-learning-with-keras-from-benjamin-young-9781091838826","title":"Deep Learning with Keras from Scratch","description":"\u003cp\u003e\u003cb\u003eSummary\u003c\/b\u003e\u003c\/p\u003e\u003cp\u003eDo you want to grasp deep learning technologies quickly and effectively even without any machine learning background?\u003c\/p\u003e\u003cp\u003eDo you want to understand many state-of-art deep learning techniques with bare-minimum math?\u003c\/p\u003e\u003cp\u003eDo you have obstacles to implement a real-life deep learning projects even with easy to use Keras?\u003c\/p\u003e\u003cp\u003eThis book will ease these pains and help you learn and grasp deep learning technology from ground zero with many interesting real-world examples implemented in Keras\/TensorFlow with simple and intuitive syntax.In this book, you will learn: \u003c\/p\u003e\u003cp\u003e* a basic deep learning concepts\/theory with bare-minimum math* a deep-dived\/well-explained MNIST CNN example so that you can really understand Keras sequential model, how to choose loss, optimizer, metrics in Keras etc.\u003c\/p\u003e\u003cp\u003e* how to use a pre-trained model by using transfer learning\/fine-tune techniques.\u003c\/p\u003e\u003cp\u003e* what are CNN, RNN, Seq2Seq, word embedding, CTC, Auto-encoder, DMN, DQN\/DDQN, MCTS, Alphago\/Alphazero etc, and how they work.\u003c\/p\u003e\u003cp\u003e* How those deep learning technologies are applied to NLP, OCR, Speech, Computer Games etc.\u003c\/p\u003e\u003cp\u003e\u003cb\u003eDescription\u003c\/b\u003e\u003c\/p\u003e\u003cp\u003eArtificial Intelligence (AI), Machine Learning especially Deep Learning has made tremendous progress in recent years. It starts to spread to all industries.\u003c\/p\u003e\u003cp\u003eQuote from Andrew Ng, a famous AI researcher: \"AI is the new electricity. About 100 years ago, electricity transformed every major industry. AI has advanced to the point where it has the power to transform every major sector in coming years.\"\u003c\/p\u003e\u003cp\u003eUnless you are a refresh graduated student with AI\/deep learning major, many of us do not have a formal machine learning\/deep learning training before, so it is time to keep updated with latest technology.\u003c\/p\u003e\u003cp\u003eKeras is a very popular, easy to use, yet powerful deep learning framework that promotes a simple and intuitive syntax. But if you do not have much deep learning background, you will find difficulties to really understand the keras codes and have obstacles to implement real-life deep learning projects effectively in keras.This book will help you learn and grasp deep learning technology from ground zero with many interesting real world examples using python\/keras\/tensorflow. It covers many state-of-art deep learning technologies, e.g.: Convoluational neural network (CNN), Recurrent neural network (RNN), Seq2Seq model, word emedding, Connectionist temporal calssification (CTC ), Auto-encoder, Dynamic Memrory Network (DMN), Deep-Q-learning(DQN\/DDQN), Monte Carlo Tree search (MCTS), Alphago\/Alphazero etc. The books could also be used as a quick guide on how to use and understand deep learning in the real life.\u003c\/p\u003e\u003cp\u003eReaders should have basic knowledge of python, scripting etc. Any constructive feedback is welcome. \u003c\/p\u003e\u003cp\u003eFree lifetime upgrade ( for an electronic copy ) as the book has been and will be frequently updated according to readers' feedback. Please feel free to contact the author.\u003c\/p\u003e\u003cp\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003c\/p\u003e\u003col\u003e\n\u003cli\u003eIntroduction\u003c\/li\u003e\n\u003cli\u003eWhat is deep learning\u003c\/li\u003e\n\u003cli\u003eDeep neural network basic concepts\u003c\/li\u003e\n\u003cli\u003ePython and NumPy basic\u003c\/li\u003e\n\u003cli\u003eDeep learning development environments\u003c\/li\u003e\n\u003cli\u003eMNIST CNN example: A deep dive of how to handle image data\u003c\/li\u003e\n\u003cli\u003ePre-trained model, transfer learning and fine-tuning\u003c\/li\u003e\n\u003cli\u003eRecurrent neural network - how to handle sequences data\u003c\/li\u003e\n\u003cli\u003eNatural Language Processing\u003c\/li\u003e\n\u003cli\u003eOptical character recognition\u003c\/li\u003e\n\u003cli\u003eAudio processing, speech processing\u003c\/li\u003e\n\u003cli\u003eAutoencoder network\u003c\/li\u003e\n\u003cli\u003eDeep reinforcement learning\u003c\/li\u003e\n\u003cli\u003eLearning from scratch (self-play) AlphaZero\u003c\/li\u003e\n\u003cli\u003eHow to deploy deep learning model.\u003c\/li\u003e\n\u003c\/ol\u003e\u003cp\u003e\u003cb\u003eNote\u003c\/b\u003e\u003c\/p\u003e\u003cp\u003ePytorch version of this book (Pytorch Deep Learning by Example) could be found at: https: \/\/www.amazon.com\/dp\/B08JKQLB8Z\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAuthor:\u003c\/b\u003e Benjamin Young\u003cbr\u003e\u003cb\u003eISBN-10:\u003c\/b\u003e 1091838828\u003cbr\u003e\u003cb\u003eISBN-13:\u003c\/b\u003e 9781091838826\u003cbr\u003e\u003cb\u003ePublisher:\u003c\/b\u003e Independently Published\u003cbr\u003e\u003cb\u003eLanguage:\u003c\/b\u003e English\u003cbr\u003e\u003cb\u003ePublished:\u003c\/b\u003e 03\/28\/2019\u003cbr\u003e\u003cb\u003ePages:\u003c\/b\u003e 416\u003cbr\u003e\u003cb\u003eFormat:\u003c\/b\u003e Paperback\u003cbr\u003e\u003cb\u003eWeight:\u003c\/b\u003e 1.81lbs\u003cbr\u003e\u003cb\u003eSize:\u003c\/b\u003e 10.00h x 7.99w x 0.85d","brand":"Benjamin Young","offers":[{"title":"Paperback","offer_id":47200101269759,"sku":"9781091838826","price":39.99,"currency_code":"USD","in_stock":true}],"url":"https:\/\/www.whiterainbookhouse.com\/products\/deep-learning-with-keras-from-benjamin-young-9781091838826","provider":"WR Book House","version":"1.0","type":"link"}