NLP Base Camp

Hey, I’m Chris McCormick. I help researchers, students, and developers like you to master the most challenging subjects in NLP, and to jump start your projects with easy-to-read eBooks, video tutorials, and example code.

A "base camp" provides equipment and supplies for people before setting off on their adventures...

In the same way, NLP Base Camp will help you understand the fundamental concepts you need and supply easy-to-follow example code that together can provide a smooth start for your next NLP project. 

 

 

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All Access Membership

A monthly base camp membership grants you access to ALL of my existing content, plus new tutorials I continue to publish. This includes:

Videos

Video Lectures & Code Walkthroughs with colorful illustrations to help guide you through new concepts.

 

eBooks

eBooks offer deep-dives into the details of the architectures of word2vec, BERT, and multiple BERT variants.

Example Code

Tutorials and example code for a wide variety of common BERT use-cases will help jump start your own project.

Membership also includes...

Topical Index

Easily find help for your topic. The index organizes all of my content, and recommends resources for additional topics.

Research Group Recordings

Nick and I host a research group 2-3 times a month to share our progress on our current research topic. Join us on Thursdays! Base Camp members also have access to the session recordings!

Ready to learn a whole new skill?

Hi, I'm Chris McCormick

I'm an author of eBooks, tutorial videos, and example code on a variety of Machine Learning topics--particularly on challenging subjects in NLP.

I'm best known for word2vec blog posts  (recommended reading for Stanford's NLP class), BERT architecture YouTube series, and example code for a variety of BERT applications. 

I earned my B.S. from Stanford in 2006 as a software engineer, and have been working in the areas of computer vision, machine learning, and NLP since 2012.

Style

My writing and speaking styles are characterized by levity and positioning myself as a fellow learner rather than an authority.

I love to create the tutorials that I wish I could have read--with an emphasis on thoroughness, while still being easy-to-follow.

Illustrations

I'm no graphic artist, but I do find that simple and colorful illustrations can aid greatly in an explanation, and keep you engaged in the learning process. 

You'll often find my illustrations reused around the web. 

I enjoy creating them and always end up wishing I could add more!

Example Code

 

It's usually not hard to find example code on the web, but it's rare that you'll find code that's well organized and commented, and that makes it clear what it does and doesn't do.

Colab Notebooks are a wonderful teaching tool because they allow me to:

  1. Divide code into (collapsible!) sections, with an outline in the sidebar.
  2. Insert formatted text cells and illustrations to help explain what's going on.

Beyond that, I like my code to be abundantly easy to read, and so it's rare to find a line of my code without a verbal explanation of what it does. (In other words, my code is thoroughly commented!)

 

Testimonials

Frequently Asked Questions

The majority of my content is focused on BERT and related models. 

You'll find thorough tutorials on the architecture of BERT and how to apply it.

You'll also find tutorials on how to apply BERT to a variety of applications:

  • Document Classification, including multiclass and multi-label.
  • Question Answering
  • Domain-specific text
  • Non-English applications
  • Named Entity Recognition
  • Combining text with other feature types
  • Variants of BERT 
  • ...

After BERT, the next topic with the most coverage is word2vec, with a video course, eBook, and example code.

Code is written in Python and shared in the form of Google Colaboratory Notebooks.

BERT examples are built on PyTorch and the 'transformers' library from huggingface.

With a few exceptions, my tutorials are not available to purchase individually or as a bundle.

However, you are always welcome to become a member for as many months as you need to go through the content that you are interested in. You are free to cancel your membership at any time. 

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