Getting Started with NLP Deep Learning Using PyTorch and fastai

This course will teach you how to start using fastai library and PyTorch to obtain near-state-of-the-art results with Deep Learning NLP for text classification. It will give you a theoretical background and show how to take models to production.

In this course, Getting Started with NLP Deep Learning Using PyTorch and fastai, we'll have a look at the amazing fastai library, built on top of the PyTorch Deep Learning Framework, to learn how to perform Natural Language Processing (NLP) with Deep Neural Networks, and how to achieve some of the most recent state-of-the-art results in text classification. First, we’ll learn how to train a model for text classification very quickly, thanks to the fastai library and transfer learning. Next, we'll explore some of the theory behind Deep Learning NLP techniques, and how to deploy our models to production in Microsoft Azure. Finally, we’ll discover how to train a custom language model from scratch. When you’re finished with this course, you’ll know why fastai and PyTorch are great frameworks, how to train deep learning models for NLP tasks on your own datasets, and how to bring them to production.

• Course Overview 1min
• Exploring the fastai Library 9mins
• Setting up a Development Environment 10mins
• Building a Text/Topic Classifier with Transfer Learning 36mins
• Using Deep Learning for NLP 34mins
• Going from Prototype to Production 18mins
• Building a Custom Language Model from Scratch 14mins
• Recapping and Next Steps 6mins