Learning Path Deep Learning with R for Beginners

Mark Hodnett, Joshua F. Wiley, Yuxi (Hayden) Liu, Pablo Maldonado · Packt Publishing · 2019-05-17

This 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. By 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.

ISBN
9781838642709
출판일
2019-05-17
출판사
Packt Publishing
저자
Mark Hodnett, Joshua F. Wiley, Yuxi (Hayden) Liu, Pablo Maldonado