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Published inOct 2021
PublisherPackt
ISBN-139781801077057
Edition1st Edition
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Authors (2):
Xiaoquan Kong
Xiaoquan Kong
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Xiaoquan Kong

Xiaoquan is a machine learning expert specializing in NLP applications. He has extensive experience in leading teams to build NLP platforms in several Fortune Global 500 companies. He is a Google developer expert in Machine Learning and has been actively involved in contributions to TensorFlow for many years. He also has actively contributed to the development of the Rasa framework since the early stage and became a Rasa Superhero in 2018. He manages the Rasa Chinese community and has also participated in the Chinese localization of TensorFlow documents as a technical reviewer.
Read more about Xiaoquan Kong

Guan Wang
Guan Wang
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Guan Wang

Guan is currently working on Al applications and research for the insurance industry. Prior to that, he was a machine learning researcher at several industry Al labs. He was raised and educated in Mainland China, lived in Hong Kong for 10 years before relocating to Singapore in 2020. Guan holds BSc degrees in Physics and Computer Science from Peking University, and an MPhil degree in Physics from HKUST. Guan is an active tech blogger and community contributor to open source projects including Rasa, receiving more than10,000 stars for his own projects on Github.
Read more about Guan Wang

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Overview of Rasa NLU components

Rasa NLU is a pipeline-based general framework. This gives Rasa great flexibility.

A pipeline defines the data processing order for each component. There are dependencies between certain components. One failure in such dependency requirements will fail the whole pipeline. Rasa NLU checks the dependency requirements for each and every component. If any of those dependency requirements fail, Rasa will stop the program and give corresponding errors and warnings.

One NLU application normally includes both an intent recognition task and entity extraction task. To accomplish those tasks, here is a typical Rasa NLU pipeline:

Figure 2.3 – A typical Rasa NLU pipeline

Let's look at the components within this typical Rasa NLU pipeline:

  • Language model component: This loads the language model files to support the following components. For example, spaCy and MITIE can be initiated here.
  • Tokenizer component: This...
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Conversational AI with Rasa
Published in: Oct 2021Publisher: PacktISBN-13: 9781801077057

Authors (2)

author image
Xiaoquan Kong

Xiaoquan is a machine learning expert specializing in NLP applications. He has extensive experience in leading teams to build NLP platforms in several Fortune Global 500 companies. He is a Google developer expert in Machine Learning and has been actively involved in contributions to TensorFlow for many years. He also has actively contributed to the development of the Rasa framework since the early stage and became a Rasa Superhero in 2018. He manages the Rasa Chinese community and has also participated in the Chinese localization of TensorFlow documents as a technical reviewer.
Read more about Xiaoquan Kong

author image
Guan Wang

Guan is currently working on Al applications and research for the insurance industry. Prior to that, he was a machine learning researcher at several industry Al labs. He was raised and educated in Mainland China, lived in Hong Kong for 10 years before relocating to Singapore in 2020. Guan holds BSc degrees in Physics and Computer Science from Peking University, and an MPhil degree in Physics from HKUST. Guan is an active tech blogger and community contributor to open source projects including Rasa, receiving more than10,000 stars for his own projects on Github.
Read more about Guan Wang