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.
Course info
Level
Intermediate
Updated
Mar 21, 2019
Duration
2h 13m
Table of contents
Course Overview
Exploring the fastai Library
Setting up a Development Environment
Building a Text/Topic Classifier with Transfer Learning
Using Deep Learning for NLP
Going from Prototype to Production
Building a Custom Language Model from Scratch
Recapping and Next Steps
Description
Course info
Level
Intermediate
Updated
Mar 21, 2019
Duration
2h 13m
Description

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.

About the author
About the author

Gianni is an R&D Senior Software Engineer in Deltatre's Innovation Lab, based in Italy. A Microsoft MVP since 2011, he has been focused on emerging technologies, AI, and Virtual/Augmented/Mixed Reality since 2013.

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