Transfer learning refers to the re-use of a trained machine learning model for a similar problem, keeping the model architecture unchanged, but potentially altering the model’s weights. In this course, Expediting Deep Learning with Transfer Learning: PyTorch Playbook, you will gain the ability to identify the right approach to transfer learning, and implement it using PyTorch. First, you will learn how different forms of transfer learning – such as inductive, transductive, and unsupervised transfer learning – can be applied to different combinations of source and target domains. Next, you will discover how transfer learning solutions leverage the fact that lower layers of pre-trained models typically extract feature information and are data-specific, while later layers tend to be more problem-specific. Finally, you will explore how to design and implement the correct strategy for freezing and fine-tuning the appropriate layers of your pre-trained model. You will round out the course by seeing how various powerful architectures are made available, in pre-trained form, in PyTorch’s suite of transfer learning solutions. When you’re finished with this course, you will have the skills and knowledge to choose the right transfer learning approach to your specific problem, and design and implement it using PyTorch.
Author Name: Janani Ravi
Author Description:
Janani has a Masters degree from Stanford and worked for 7+ years at Google. She was one of the original engineers on Google Docs and holds 4 patents for its real-time collaborative editing framework. After spending years working in tech in the Bay Area, New York, and Singapore at companies such as Microsoft, Google, and Flipkart, Janani finally decided to combine her love for technology with her passion for teaching. She is now the co-founder of Loonycorn, a content studio focused on providing … more

Table of Contents

• Course Overview
  1min
• Getting Started with Transfer Learning
  48mins
• Performing Feature Extraction Using Transfer Learning
  35mins
• Reusing Model Architectures and Designs
  21mins