{"product_id":"deep-learning-with-r-for-beginners-pstrong-design-neural-network-models-in-r-3-5-using-tensorflow-keras-and-mxnet-p","title":"Deep Learning with R for Beginners","description":"\u003cp style=\"margin: 0px 0px 14px; padding: 0px; font-family: \" amazon ember arial sans-serif font-size:=\"\"\u003e\u003cb\u003eExplore the world of neural networks by building powerful deep learning models using the R ecosystem\u003c\/b\u003e\u003c\/p\u003e\u003ch4 style=\"margin: 0px; padding: 0px 0px 4px; font-family: Arial, sans-serif; text-rendering: optimizelegibility; font-size: 14px;\"\u003e\u003cstrong\u003eKey Features\u003c\/strong\u003e\u003c\/h4\u003e\u003cul style=\"margin: 0px 0px 18px 20px; padding-right: 0px; padding-left: 0px; font-family: \" amazon ember arial sans-serif font-size:=\"\"\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eGet to grips with the fundamentals of deep learning and neural networks\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eUse R 3.5 and its libraries and APIs to build deep learning models for computer vision and text processing\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eImplement effective deep learning systems in R with the help of end-to-end projects\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch4 style=\"margin: 0px; padding: 0px 0px 4px; font-family: Arial, sans-serif; text-rendering: optimizelegibility; font-size: 14px;\"\u003e\u003cstrong\u003eBook Description\u003c\/strong\u003e\u003c\/h4\u003e\u003cp style=\"margin: 0px 0px 14px; padding: 0px; font-family: \" amazon ember arial sans-serif font-size:=\"\"\u003eDeep learning finds practical applications in several domains, while R is the preferred language for designing and deploying deep learning models.\u003c\/p\u003e\u003cp style=\"margin: -4px 0px 14px; padding: 0px; font-family: \" amazon ember arial sans-serif font-size:=\"\"\u003eThis Learning Path introduces you to the basics of deep learning and even teaches you to build a neural network model from scratch. As you make your way through the chapters, you'll explore deep learning libraries and understand how to create deep learning models for a variety of challenges, right from anomaly detection to recommendation systems. The book will then help you cover advanced topics, such as generative adversarial networks (GANs), transfer learning, and large-scale deep learning in the cloud, in addition to model optimization, overfitting, and data augmentation. Through real-world projects, you'll also get up to speed with training convolutional neural networks (CNNs), recurrent neural networks (RNNs), and long short-term memory networks (LSTMs) in R.\u003c\/p\u003e\u003cp style=\"margin: -4px 0px 14px; padding: 0px; font-family: \" amazon ember arial sans-serif font-size:=\"\"\u003eBy the end of this Learning Path, you'll be well versed with deep learning and have the skills you need to implement a number of deep learning concepts in your research work or projects.\u003c\/p\u003e\u003cp style=\"margin: -4px 0px 14px; padding: 0px; font-family: \" amazon ember arial sans-serif font-size:=\"\"\u003e\u003cstrong\u003eThis Learning Path includes content from the following Packt products:\u003c\/strong\u003e\u003c\/p\u003e\u003cul style=\"margin: 0px 0px 18px 20px; padding-right: 0px; padding-left: 0px; font-family: \" amazon ember arial sans-serif font-size:=\"\"\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eR Deep Learning Essentials - Second Edition by Joshua F. Wiley and Mark Hodnett\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eR Deep Learning Projects by Yuxi (Hayden) Liu and Pablo Maldonado\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch4 style=\"margin: 0px; padding: 0px 0px 4px; font-family: Arial, sans-serif; text-rendering: optimizelegibility; font-size: 14px;\"\u003e\u003cstrong\u003eWhat you will learn\u003c\/strong\u003e\u003c\/h4\u003e\u003cul style=\"margin: 0px 0px 18px 20px; padding-right: 0px; padding-left: 0px; font-family: \" amazon ember arial sans-serif font-size:=\"\"\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eImplement credit card fraud detection with autoencoders\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eTrain neural networks to perform handwritten digit recognition using MXNet\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eReconstruct images using variational autoencoders\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eExplore the applications of autoencoder neural networks in clustering and dimensionality reduction\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eCreate natural language processing (NLP) models using Keras and TensorFlow in R\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003ePrevent models from overfitting the data to improve generalizability\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eBuild shallow neural network prediction models\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch4 style=\"margin: 0px; padding: 0px 0px 4px; font-family: Arial, sans-serif; text-rendering: optimizelegibility; font-size: 14px;\"\u003e\u003cstrong\u003eWho this book is for\u003c\/strong\u003e\u003c\/h4\u003e\u003cp style=\"margin: 0px 0px 14px; padding: 0px; font-family: \" amazon ember arial sans-serif font-size:=\"\"\u003eThis Learning Path is for aspiring data scientists, data analysts, machine learning developers, and deep learning enthusiasts who are well versed in machine learning concepts and are looking to explore the deep learning paradigm using R. A fundamental understanding of R programming and familiarity with the basic concepts of deep learning are necessary to get the most out of this Learning Path.\u003c\/p\u003e\u003ch4 style=\"margin: 0px; padding: 0px 0px 4px; font-family: Arial, sans-serif; text-rendering: optimizelegibility; font-size: 14px;\"\u003e\u003cstrong\u003eTable of Contents\u003c\/strong\u003e\u003c\/h4\u003e\u003col style=\"color: rgb(136, 136, 136); margin-top: 0px; margin-right: 0px; margin-left: 22px; padding-right: 0px; padding-left: 0px; font-family: \" amazon ember arial sans-serif font-size:=\"\" margin-bottom:=\"\"\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003e\u003cspan style=\"color:#000000;\"\u003eGetting Started with Deep Learning\u003c\/span\u003e\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003e\u003cspan style=\"color:#000000;\"\u003eTraining a Prediction Model\u003c\/span\u003e\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003e\u003cspan style=\"color:#000000;\"\u003eDeep Learning Fundamentals\u003c\/span\u003e\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003e\u003cspan style=\"color:#000000;\"\u003eTraining Deep Prediction Models\u003c\/span\u003e\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003e\u003cspan style=\"color:#000000;\"\u003eImage Classification Using Convolutional Neural Networks\u003c\/span\u003e\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003e\u003cspan style=\"color:#000000;\"\u003eTuning and Optimizing Models\u003c\/span\u003e\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003e\u003cspan style=\"color:#000000;\"\u003eNatural Language Processing Using Deep Learning\u003c\/span\u003e\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003e\u003cspan style=\"color:#000000;\"\u003eDeep Learning Models Using TensorFlow in R\u003c\/span\u003e\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003e\u003cspan style=\"color:#000000;\"\u003eAnomaly Detection and Recommendation Systems\u003c\/span\u003e\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003e\u003cspan style=\"color:#000000;\"\u003eRunning Deep Learning Models in the Cloud\u003c\/span\u003e\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003e\u003cspan style=\"color:#000000;\"\u003eThe Next Level in Deep Learning\u003c\/span\u003e\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003e\u003cspan style=\"color:#000000;\"\u003eHandwritten Digit Recognition Using Convolutional Neural Networks\u003c\/span\u003e\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003e\u003cspan style=\"color:#000000;\"\u003eTraffic Sign Recognition for Intelligent Vehicles\u003c\/span\u003e\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003e\u003cspan style=\"color:#000000;\"\u003eFraud Detection with Autoencoders\u003c\/span\u003e\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003e\u003cspan style=\"color:#000000;\"\u003eText Generation Using Recurrent Neural Networks\u003c\/span\u003e\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003e\u003cspan style=\"color:#000000;\"\u003eSentiment Analysis with Word Embeddings\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ol\u003e","brand":"Packt Publishing","offers":[{"title":"Default Title","offer_id":50506200809542,"sku":"9781838642709","price":2959.2,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0754\/2797\/1142\/files\/smaller_bwag-x2.png?v=1790322878","url":"https:\/\/cb-india.com\/products\/deep-learning-with-r-for-beginners-pstrong-design-neural-network-models-in-r-3-5-using-tensorflow-keras-and-mxnet-p","provider":"Computer Bookshop (India) Pvt Ltd","version":"1.0","type":"link"}