Transfer Learning: Understand the Big Picture & Make the Right Choices for Your Use Case
This article is a guide for better understanding transfer learning with intuitive examples.
Published in
7 min readMar 12, 2021
Training a deep neural network from scratch is not an easy task, and might not always be the right thing to do because of the complexity that could go with the different tasks such as finding the right amount the data for the problem to be solved, preprocessing, and designing a model that performs better for our problem. On the other hand, we can use transfer learning to help us “stand on the shoulders of giants”. In this article we will discuss the following topics:
- Transfer learning, what it is about
- Difference between transfer learning and the traditional Machine Learning
- Different categories of transfer learning
- Different ways of using transfer learning
- The main benefits of using transfer learning
Transfer learning, what it is about
It is the process of re-using deep-neural networks that have been typically pre-trained on a huge corpus of data, and also evaluated to work very well on certain problems.
