{"product_id":"r-deep-learning-cookbook-solve-complex-neural-net-problems-with-tensorflow-h2o-and-mxnet-paperback","title":"R Deep Learning Cookbook: Solve complex neural net problems with TensorFlow, H2O and MXNet - Paperback","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003ePks Prakash\u003c\/b\u003e (Author), \u003cb\u003eAchyutuni Sri Krishna Rao\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003ePowerful, independent recipes to build deep learning models in different application areas using R libraries \u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eKey Features: \u003c\/strong\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eMaster intricacies of R deep learning packages such as mxnet \u0026amp; tensorflow\u003c\/li\u003e\n\u003cli\u003eLearn application on deep learning in different domains using practical examples from text, image and speech\u003c\/li\u003e\n\u003cli\u003eGuide to set-up deep learning models using CPU and GPU\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eBook Description: \u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003eDeep Learning is the next big thing. It is a part of machine learning. It's favorable results in applications with huge and complex data is remarkable. Simultaneously, R programming language is very popular amongst the data miners and statisticians.\u003c\/p\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003eThis book will help you to get through the problems that you face during the execution of different tasks and Understand hacks in deep learning, neural networks, and advanced machine learning techniques. It will also take you through complex deep learning algorithms and various deep learning packages and libraries in R. It will be starting with different packages in Deep Learning to neural networks and structures. You will also encounter the applications in text mining and processing along with a comparison between CPU and GPU performance.\u003c\/p\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003eBy the end of the book, you will have a logical understanding of Deep learning and different deep learning packages to have the most appropriate solutions for your problems.\u003c\/p\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWhat You Will Learn: \u003c\/strong\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eBuild deep learning models in different application areas using TensorFlow, H2O, and MXnet.\u003c\/li\u003e\n\u003cli\u003eAnalyzing a Deep boltzmann machine\u003c\/li\u003e\n\u003cli\u003eSetting up and Analysing Deep belief networks\u003c\/li\u003e\n\u003cli\u003eBuilding supervised model using various machine learning algorithms\u003c\/li\u003e\n\u003cli\u003eSet up variants of basic convolution function\u003c\/li\u003e\n\u003cli\u003eRepresent data using Autoencoders.\u003c\/li\u003e\n\u003cli\u003eExplore generative models available in Deep Learning.\u003c\/li\u003e\n\u003cli\u003eDiscover sequence modeling using Recurrent nets\u003c\/li\u003e\n\u003cli\u003eLearn fundamentals of Reinforcement Leaning\u003c\/li\u003e\n\u003cli\u003eLearn the steps involved in applying Deep Learning in text mining\u003c\/li\u003e\n\u003cli\u003eExplore application of deep learning in signal processing\u003c\/li\u003e\n\u003cli\u003eUtilize Transfer learning for utilizing pre-trained model\u003c\/li\u003e\n\u003cli\u003eTrain a deep learning model on a GPU\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWho this book is for \u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003eData science professionals or analysts who have performed machine learning tasks and now want to explore deep learning and want a quick reference that could address the pain points while implementing deep learning. Those who wish to have an edge over other deep learning professionals will find this book quite useful.\u003c\/p\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 288\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.6 x 9.25 x 7.5 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e August 04, 2017\u003c\/div\u003e\n            ","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":48336188604665,"sku":"9781787121089","price":73.42,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0789\/2782\/3097\/files\/3LMHR2tEwD9781787121089.webp?v=1777518043","url":"https:\/\/bookscloud.io\/products\/r-deep-learning-cookbook-solve-complex-neural-net-problems-with-tensorflow-h2o-and-mxnet-paperback","provider":"BooksCloud Book Dropshipping","version":"1.0","type":"link"}