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Introduction to Deep Learning Using R

. 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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Advanced Deep Learning with R

Discover best practices for choosing, building, training, and improving deep learning models using Keras-R, and TensorFlow-R libraries Key;

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R Deep Learning Essentials

looking to explore the deep learning paradigm using the packages available in R. You should have a fundamental understanding of the R language and;

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Deep Learning with R for Beginners

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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R Deep Learning Essentials

of neural networks by building powerful deep learning models using the R ecosystem. This book will introduce you to the basic principles of deep;

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Hands-On Deep Learning with R

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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R Deep Learning Cookbook

Powerful, independent recipes to build deep learning models in different application areas using R libraries About This Book * Master;

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Machine Learning Using R

Examine the latest technological advancements in building a scalable machine-learning model with big data using R. This second edition;

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Deep Learning with R Cookbook

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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Machine Learning with R

learning book, updated and improved for R 3.6 and beyond Harness the power of R to build flexible, effective, and transparent machine learning;

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Practical MATLAB Deep Learning

provides an introduction to deep learning and using MATLAB's deep-learning toolboxes. In this book, you'll see how these toolboxes provide the;

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Practical MATLAB Deep Learning

provides an introduction to deep learning and using MATLAB's deep-learning toolboxes. In this book, yoüll see how these toolboxes provide the;

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R Deep Learning Projects

5 real-world projects to help you master deep learning concepts Key Features Master the different deep learning paradigms and build real;

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Hands-On Machine Learning with R

apply the machine learning stack within R, which includes using various R packages such as glmnet, h2o, ranger, xgboost, keras, and others to;

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Mastering Machine Learning with R -

networks, you will explore deep learning, and more. By the end of this book, you will be able to perform machine learning with R in the cloud using;

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Deep Learning with Microsoft Cognitive Toolkit Quick Start Guide

will be a quick introduction to using Cognitive Toolkit and will teach you how to train and validate different types of neural networks, such;

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Beginning Anomaly Detection Using Python-Based Deep Learning

statistical and traditional machine learning methods for anomaly detection using Scikit-Learn in Python, the book then provides an introduction to;

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The Deep Learning with PyTorch Workshop

network architecture in deep learning Implement helpful methods to create and train a model using PyTorch syntax Discover how intelligent;

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Supervised Machine Learning for Text Analysis in R

workflows for predictive modeling using text as features Compare traditional machine learning methods and deep learning methods for text data;

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Supervised Machine Learning for Text Analysis in R

workflows for predictive modeling using text as features Compare traditional machine learning methods and deep learning methods for text data;

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Deep Learning for Data Analytics

, biomedical engineering, and object tracking using deep learning methodologies. The book provides a pragmatic direction for researchers who wish to;

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TensorFlow 2 Reinforcement Learning Cookbook

Discover recipes for developing AI applications to solve a variety of real-world business problems using reinforcement learning Key;

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Pro Deep Learning with TensorFlow

quickly using TensorFlow and to optimize different deep learning architectures. All of the practical aspects of deep learning that are relevant;

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Behavior Analysis with Machine Learning Using R

Behavior Analysis with Machine Learning Using R introduces machine learning and deep learning concepts and algorithms applied to a diverse;

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Learning Bayesian Models with R: Become an expert in Bayesian Machine Learning methods using R and apply them to solve real-world big data problems

Become an expert in Bayesian Machine Learning methods using R and apply them to solve real-world big data problems About This Book;

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Deep Learning for NLP and Speech Recognition

learning techniques to NLP and speech and provides insights into using the tools and libraries for real-world applications. Deep Learning for NLP;

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Deep Learning for Nlp and Speech Recognition

learning techniques to NLP and speech and provides insights into using the tools and libraries for real-world applications. Deep Learning for NLP;

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