Rasa NLU

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.…

Karen White

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.…

Tobias Wochinger

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.…

Tobias Wochinger

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…

Dominik Rosenkranz

Rasa NLU in Depth: Part 1 – Intent Classification

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.…

Justina Petraityte

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.…

Tyler Hughes

How to handle multiple intents per input using Rasa NLU TensorFlow pipeline

In this post we are going to take a comprehensive look at how we can use Rasa NLU TensorFlow pipeline to build chatbots which can understand multiple intents per input.…

Justina Petraityte