Machine Learning

How to Get Started with Deep Learning for Natural Language Processing

Last Updated on August 14, 2020

Deep Learning for NLP Crash Course.

Bring Deep Learning methods to Your Text Data project in 7 Days.

We are awash with text, from books, papers, blogs, tweets, news, and increasingly text from spoken utterances.

Working with text is hard as it requires drawing upon knowledge from diverse domains such as linguistics, machine learning, statistical methods, and these days, deep learning.

Deep learning methods are starting to out-compete the classical and statistical methods on some challenging natural language processing problems with singular and simpler models.

In this crash course, you will discover how you can get started and confidently develop deep learning for natural language processing problems using Python in 7 days.

This is a big and important post. You might want to bookmark it.

Kick-start your project with my new book Deep Learning for Natural Language Processing, including step-by-step tutorials and the Python source code files for all examples.

Let’s get started.

  • Update Jan/2020: Updated API for Keras 2.3 and TensorFlow 2.0.
  • Update Aug/2020: Updated link to movie review dataset.
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