Learn how to solve practical NLP problems with the Flair Python framework, train sequence labeling models, work with text classifiers and word embeddings, and much more through hands-on practical exercises
Purchase of the print or Kindle book includes a free PDF eBook
What’s inside
- Practical know-how, backed by the community and written by an NLP expert
- Insights into basic NLP problems and terminology
- Ways of solving real-world NLP problems with Flair and hands-on exercises
You’ll get the most out of this book if
- You want to learn about NLP through one of the most beginner-friendly, yet powerful Python NLP libraries out there
- You’re a software engineering student, developer, data scientist, or are transitioning into NLP and are interested in learning about practical approaches to solving problems with Flair
- You’re not looking for in-depth theoretical understanding of the mathematics behind NLP
- You have beginner-level knowledge of Python programming, which is a prerequisite
What your journey will look like
From installing Flair and learning about the basic NLP concepts and terminology, this book takes a hands-on approach to explaining and solving real-world NLP problems. After exploring Flair's extensive features, such as sequence tagging, text classification, and word embeddings through practical exercises, you'll tackle topics like training your own sequence, labeling and text classification models, and using hyperparameter tuning in order to choose the right training parameters. By the end of this book, you’ll have a solid grasp on Flair and the problems you can solve with it.
Some of the things you’ll learn from this book
- Understanding the core NLP terminology and concepts
- A firm grasp on the capabilities of the Flair NLP framework
- Using Flair's state-of-the-art pre-built models with ease
- Building custom sequence labeling models, embeddings, and classifiers
- Learning about a novel text classification technique called TARS
- How to build applications with Flair and how to deploy them to production
Table of Contents
- Introduction to Flair
- Flair Base Types
- Embeddings in Flair
- Sequence Tagging
- Training Sequence Labeling Models
- Hyperparameter Optimization in Flair
- Training Your Own Embeddings
- Text Classification in Flair
- Deploying and Using Models in Production
- Hands-on exercise – Building a trading bot with Flair
Tadej Magajna is a former lead machine learning engineer, former data scientist, master of Computer Science and now a software engineer at Microsoft. He currently works in a team responsible for language model training and building language packs for keyboards. He started his career as a 15-year-old at a local media company as a web developer and progressed towards more complex engineering and machine learning problems. He tackled problems like NLP market research, public transport bus and train capacity forecasting and finally language model training at his current role. Today, he is based in his hometown Ljubljana, Slovenia.
