R Deep Learning Cookbook

Introduction

A lot of development has happened within the deep learning domain in recent years, to enhance algorithmic efficacy and computational efficiency across different domains such as text, images, audio, and video. However, when it comes to training on new datasets, machine learning usually rebuilds the model from scratch, as is done in traditional data science problem solving. This becomes challenging when a new big dataset need to be trained as it will require very high computation power a lot of and time to reach the desired model efficacy.

Transfer Learning is a mechanism to learn new scenarios from existing models. This approach is very useful to train on big datasets, not necessarily from a similar domain or problem statement. ...