If you want to build, iterate and scale NLP systems in a business setting and to tailor them for various industry verticals, this is your guide.
Consider the task of building a chatbot or text classification system at your organization. In the beginning, there may be little or no data to work with. At this point, a basic solution that uses rule based systems or traditional machine learning will be apt. As you accumulate more data, more sophisticated—and often data intensive—ML techniques can be used including deep learning. At each step of this journey, there are dozens of alternative approaches you can take. This book helps you navigate this maze of options.
Table of Contents
- 1. NLP: A Primer
2. Text Classification
- A taxonomy of text classification
- A Pipeline for Building Text Classification Systems
- One Pipeline, Many Classifiers
- Deep Learning for Text Classification
- Learning with Less (or No) Data, and Adapting to New Domains
- Practical Advice
3. NLP in e-Commerce
- Building an e-commerce catalogue
- Review analysis
- Recommendation for e-commerce
- Search in E-Commerce
- Building an E-Commerce Catalogue
- Review Analysis
- Recommendations for e-Commerce
- Title: Practical Natural Language Processing
- Release date: May 2020
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 9781492054047