Rasa Open Source + Rasa X: Better Together
We recently launched Rasa X, a free toolset that helps you quickly iterate on and improve the quality of your contextual assistant built using Rasa Open Source.…
NLP vs. NLU: What's the Difference and Why Does it Matter?
The terms NLP and NLU are often used interchangeably, but they have slightly different meanings. Learn the difference between natural language processing and natural language understanding and why they're important for successful conversational applications.…
A Look Back at Rasa Developer Summit 2019
During two panel discussions and 14 talks, we heard from speakers at companies including N26, Adobe, Lemonade, and Facebook, who related experiences building custom integrations, shared cutting-edge research, and outlined strategies for leading effective product teams.…
Rasa NLU in Depth: Part 3 – Hyperparameter Tuning
Part 3 of our Rasa NLU in Depth series covers hyperparameter tuning. We will explain how to use Docker containers to run a Rasa NLU hyperparameter search for the best NLU pipeline at scale.…
Rasa NLU in Depth: Part 2 – Entity Recognition
Part 2 of our Rasa NLU in Depth series covers entity recognition. We will explain which components you should use for which type of entity and how to tackle common problems like fuzzy entities.…
How to build HIPAA compliant AI Assistants using Rasa
TL;DR: Rasa provides a way to develop your HIPAA compliant conversational AI Assistants. It gives you the full functionality and flexibility to build scalable contextual…
Enhancing Rasa NLU models with Custom Components
We believe that customizing ML models is crucial for building successful AI assistants. In this tutorial, you will learn how to implement custom components and add them to the Rasa NLU pipeline.…
Improving Entity Extraction with Lookup Tables
Extracting meaning from text is at the core of any NLU system. Rasa NLU + Lookup tables can dramatically improve entity extraction for your application.…