Natural Language Processing in Python

Practical techniques for preparing text for custom search, content recommenders, AI applications, and more…

I’m teaching a sequence of courses that take Python programmers through an introduction to popular NLP tools and techniques, on through more advanced group projects incorporating NLP and ML, then finally through an intro to AI. Each course has a limit of 300 people, and these fill up quickly — they’re also being repeated bi-monthly.

Get Started with NLP in Python

If you’re new to NLP, this course will provide you with initial hands-on work: the confidence to explore much further into use of Deep Learning with text, natural language generation, chatbots, etc. First, however, we’ll show you how to prepare text for parsing, how to extract key phrases, prepare text for indexing in search, calculate similarity between documents, etc.

This first course in my new series is for you because…

  • You’re a Python programmer and need to learn how to use available NLP packages
  • You’re a data scientist with some Python experience and need to leverage NLP and text mining
  • You are interested in chatbots, deep learning, and related AI work, and want to understand the basics for handling text data in those use cases

Upcoming: (will keep updated)

Previous:

Hands-on course materials are based on Jupyter notebooks, which O’Reilly Media hosts on JupyterHub:

The course materials include instructions for installing Python libraries, and we also have a Docker container available which includes all the dependencies.


Backstory

In late November 2016, we launched a new program at O’Reilly Media to introduce live online training in Safari. Although we’d produced similar online courses through O’Reilly for 14 months prior, moving that exclusively into a membership model was new territory. After months of preparation, research, planning, contingencies, position papers, etc., we took a deep breath and jumped in with both feet. The result? Thousands of people registered and waitlisted for courses within the first two days. Writing nearly a month later, demand has only increased.

Keep in mind, these courses are the opposite of MOOCs. We realized how the industry had swung too far in the wrong direction with Ed Tech, how VC-backed tech startups had taken seriously detrimental short-cuts to attempt scale in learning, how current trends in “education” at scale opposed our ethos and experience at O’Reilly. Our origin story as a company was about peer teaching, with Tim and Dale active at Unix user group meetings. We’ve always been about peer teaching — that’s one reason I was eager to lead this program, calling back to my teaching fellowship many years ago at Stanford, where I’d helped establish a popular peer teaching program there.