In this tutorial, we will give you some deeper insights into recent developments in the field of Deep Learning NLP. The first part of the workshop will be an introduction into the dynamic deep learning library PyTorch. We will explain the key steps for building a basic model. In the second part, we will introduce how to implement more advanced architectures and apply it to real world datasets.

SLIDES: https://docs.google.com/presentation/d/1zyuwCx7knqnP-LJswlDfWSmk5FhFgFmYJGqdEZn8yhc/edit#slide=id.g33c734b530_0_656

REPO: https://github.com/scoutbee/pytorch-nlp-notebooks

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Further reading about PyTorch and Deep Learning

☞ A Complete Machine Learning Project Walk-Through in Python

☞ Machine Learning A-Z™: Hands-On Python & R In Data Science

☞ Deep Learning A-Z™: Hands-On Artificial Neural Networks

☞ Deep Learning With TensorFlow 2.0

☞ Deep Learning and Modern Natural Language Processing (NLP)

☞ Getting Started with Natural Language Processing in Python

☞ spaCy Cheat Sheet: Advanced NLP in Python

☞ Using Google Cloud Natural Language API with NLP

#python #deep-learning #machine-learning #data-science