Review of Stanford Course on Deep Learning for Natural Language Processing
Last Updated on August 7, 2019
Natural Language Processing, or NLP, is a subfield of machine learning concerned with understanding speech and text data.
Statistical methods and statistical machine learning dominate the field and more recently deep learning methods have proven very effective in challenging NLP problems like speech recognition and text translation.
In this post, you will discover the Stanford course on the topic of Natural Language Processing with Deep Learning methods.
This course is free and I encourage you to make use of this excellent resource.
After completing this post, you will know:
- The goal and prerequisites of this course.
- A breakdown of the course lectures and how to access the slides, notes, and videos.
- How to make best use of this material.
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.
Overview
This post is divided into 5 parts; they are:
- Course Summary
- Prerequisites
- Lectures
- Projects
- How to Best Use This Material
Course Summary
The course is taught by Chris Manning and Richard Socher.
Chris Manning is an author of at least two top
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