R Deep Learning Essentials
This book demonstrates how to use deep Learning in R for machine learning, image classification, and natural language processing. It covers topics such as convolutional networks, recurrent neural networks, transfer learning and deep learning in the cloud. By the end of this book, you will be able to apply deep learning to real-world projects.
Offered by
Difficulty Level
Intermediate
Completion Time
12h36m
Language
English
About Book
Who Is This Book For?
This second edition of R Deep Learning Essentials 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. Fundamental understanding of the R language is necessary to get the most out of this book.
R Deep Learning Essentials
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 12h36m total length
Getting Started with Deep Learning
Training a Prediction Model
Deep Learning Fundamentals
Training Deep Prediction Models
Image Classification Using Convolutional Neural Networks
Tuning and Optimizing Models
Natural Language Processing Using Deep Learning
Deep Learning Models Using TensorFlow in R
Anomaly Detection and Recommendation Systems
Running Deep Learning Models in the Cloud
The Next Level in Deep Learning
Related Resources
Access Ready-to-Use Books for Free!
Get instant access to a library of pre-built books—free trial, no credit card required. Start training your team in minutes!