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.
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.
Course Overview Hi everyone. My name is Gianni Rosa Gallina, and welcome to my course, Getting Started with NLP Deep Learning Using PyTorch and fastai. I am an R&D specialist and senior software engineer in the Innovation Lab of Deltatre, based in Italy. In this course, we are going to have a look at the amazing fastai library built on top of PyTorch deep learning framework to learn how to perform natural language processing with deep learning neural networks, how to achieve some of the most recent state-of-the-art results in this field. Some of the major topics that we will cover include data preparation for deep learning NLP, from raw text to embeddings, learn how to leverage transfer learning in NLP for classification tasks, understanding and building a custom language model, going from prototype to production once we are satisfied with our models. By the end of this course, you'll know why fastai and PyTorch are great frameworks, how it's quick and easy to train deep learning models for natural language processing tasks on your own dataset and bring them to production. Before beginning the course, you should be familiar with general machine learning and deep learning concepts, some basic Python programming and dev tools, PyTorch basics, and Microsoft Azure Machine Learning services. I hope you will join me on this journey to learn some NLP deep learning concepts with the Getting Started with NLP Deep Learning Using PyTorch and fastai course, at Pluralsight.