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Powerful, independent recipes to build deep learning models in different application areas using R libraries About This Book * Master;
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Tackle the complex challenges faced while building end-to-end deep learning models using modern R libraries Key Features Understand the;
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Discover best practices for choosing, building, training, and improving deep learning models using Keras-R, and TensorFlow-R libraries Key;
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Implement neural network models in R 3.5 using TensorFlow, Keras, and MXNet Key Features Use R 3.5 for building deep learning models for;
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Explore the world of neural networks by building powerful deep learning models using the R ecosystem Key Features Get to grips with the;
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algorithms for unsupervised data using deep learning concepts with R * Master the common problems faced such as overfitting of data, anomalous;
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in learning effective data visualization techniques with R and a wide-range of its associated libraries.;
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other previously impossible applications. Deep Learning with R is for developers and data scientists with some R experience who;
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If you want to learn how to use R for machine learning and gain insights from your data, then this book is ideal for you. Regardless;
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Explore and implement deep learning to solve various real-world problems using modern R libraries such as TensorFlow, MXNet, H2O, and;
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Comprehensive recipes to give you valuable insights on Transformers, Reinforcement Learning, and more Key Features Deep Learning;
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Deep learning doesn't have to be intimidating. Until recently, this machine-learning method required years of study, but with frameworks;
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Examine the latest technological advancements in building a scalable machine-learning model with big data using R. This second edition;
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. Introduction to Deep Learning Using R provides a theoretical and practical understanding of the models that perform these tasks by building upon the;
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learning by implementing practical projects in R will find this book a useful resource. A knowledge of R programming and the basic concepts of deep;
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This book is designed to provide a range of examples of how to extend the functionality of your R Markdown documents. As a cookbook, this;
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This book is designed to provide a range of examples of how to extend the functionality of your R Markdown documents. As a cookbook, this;
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Resolving and offering solutions to your machine learning problems with R About This Book * Implement a wide range of algorithms and;
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Discover powerful ways to effectively solve real-world machine learning problems using key libraries including scikit-learn, TensorFlow;
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Discover recipes for developing AI applications to solve a variety of real-world business problems using reinforcement learning Key;
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Solve real-world data problems with R and machine learning Key Features Third edition of the bestselling, widely acclaimed R machine;
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Master machine learning techniques with R to deliver insights in complex projects About This Book * Understand and apply machine;
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