Introduction
Language proficiency is a core metric of intelligence—not only in humans, but in machines as well. That’s why the ability to efficiently and accurately process the information conveyed by human language is so important. Natural Language Processing (NLP) technology plays an integral role in many of the recent advances in Artificial Intelligence, so it’s no surprise that it’s earning more and more of the spotlight on the intelligent technology stage. And it’s not only tech companies that are leveraging NLP; Finance, insurance, and other industries across the board are increasingly interested in the potential benefits NLP can offer. After all, language is the primary means of communication in all facets of life, and this rapidly advancing field promises to spawn countless new and exciting opportunities. There’s really never been a better time to get started with NLP!
To jumpstart your NLP education, this mini ebook features two chapters from Manning’s Getting Started with Natural Language Processing. In it, author and NLP expert Ekaterina Kochmar guides you step by step as you build two NLP applications from start to finish: one, a spam filter; the other, an information search algorithm; both, classic examples of NLP in practice that apply fundamental NLP skills and concepts. When you’re done, you’ll have valuable hands-on NLP experience that will help you hit the ground running as you continue your NLP learning.
Whether your interest in getting started with NLP is for your career, your personal passion project, or just for fun, as long as it involves textual information, you’ll find great value in this quick and practical primer. All you need to benefit from these chapters is some basic Python programming skills. We hope the information here kindles your NLP curiosity even more and opens your eyes to its endless possibilities. If you’d like to dive deeper into this highly useful, interesting—and exploding!—field, we highly recommend the complete version of Getting Started with Natural Language Processing.