{"product_id":"pytorch-deep-learning-by-example-grasp-deep-learning-from-scratch-like-alphago-zero-within-40-days-2-e-paperback","title":"Pytorch Deep Learning by Example : Grasp deep Learning from scratch like AlphaGo Zero within 40 days,2\/E  (Paperback)","description":"\u003cp\u003ePytoch is a quite powerful, flexible and yet popular deep learning framework, but the learning curve could be steep if you do not have much deep learning background or are simply from Keras background. This book will ease the pain and help you learn and grasp the latest PyTorch deep learning technology from ground zero with many interesting real-world examples. It could also be used as a quick guide on how to use and understand deep learning in real life.\u003c\/p\u003e\u003cp\u003eFree lifetime upgrade ( for an electronic copy ) as the book has been and will be frequently updated according to readers' feedbacks. Previous buyers, please feel free to contact the author for free update ( electronic copy ).\u003c\/p\u003e\u003cp\u003eDescription\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\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\u003ePytoch is a quite powerful, flexible and yet popular deep learning framework, but the learning curve could be steep if you do not have much deep learning background. This book will easy the pain and help you learn and grasp latest pytorch deep learning technology from ground zero with many interesting real world examples. 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. This book 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\u003e\u003cstrong\u003eTable of Contents\u003c\/strong\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\u003eDeep learning development environments\u003c\/li\u003e\n\u003cli\u003ePython and Tensor basic\u003c\/li\u003e\n\u003cli\u003ePytorch deep learning basic\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 Langauge 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 \u003c\/p\u003e","brand":"Independently published","offers":[{"title":"Default Title","offer_id":50506183442502,"sku":"9781089549895","price":4728.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0754\/2797\/1142\/files\/61doO2YVZbL.jpg?v=1790322283","url":"https:\/\/cb-india.com\/products\/pytorch-deep-learning-by-example-grasp-deep-learning-from-scratch-like-alphago-zero-within-40-days-2-e-paperback","provider":"Computer Bookshop (India) Pvt Ltd","version":"1.0","type":"link"}