10 Best Practices for Designing NLU Training Data
Whether you're starting from scratch or working with an existing data set, here's how to make sure your NLU training data results in accurate predictions and scales sustainably.…
New Rasa Starter Pack: Financial Services
A demo assistant you can use as a starting point for your own banking chatbot. It’s open source and free for you to copy or submit contributions.…
Usability Testing for AI Assistants
UX testing is widely used by product teams developing web, mobile, and desktop applications. The same principles apply to machine learning-based applications like AI assistants.…
Customizing Training Data Importing
Since Rasa version 1.2 you can customize the way Rasa imports training data for the model training. This tutorial shows you how to use provided out-of-the-box components or how to build your own importer module and plug it into Rasa.…
Building a Common Language for Conversational AI
We start creating a common language to talk about the structure of conversations with AI assistants.…
Designing Rasa training stories
Training data is an essential part of every machine learning model. In this post, we are going to cover the best practices of designing Rasa training stories and what you should keep in mind to build your best conversational AI assistant.…
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.…
Rasa NLU in Depth: Part 1 – Intent Classification
This is part one of our three-part in-depth series about Rasa NLU. It will cover intent classification components, when to choose which and how to solve common real-world problems.…