# The Ultimate Guide to Cognigy NLU Training

Authors name: [Sebastian Glock](/content/product-updates/author/sebastian-glock/index.html) February 14, 2022

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Many of our customers have utilized the [Intent feedback analyzer](/content/blog/intent-analyzer/index.html) to continuously improve their NLU models with tremendous success. However, at Cognigy, we are regularly asked about a more systematic approach to Intent training in projects.

So, we created a comprehensive tutorial to present a systematic technique that can be employed during the project planning process.

Visit our [Help Center Article](https://support.cognigy.com/hc/en-us/articles/4417196370834-The-Ultimate-Guide-to-Cognigy-NLU-Training) to delve deep into a systematic approach to Intent training.

In the article, you'll learn about the phases that can be used to outline the intent creation/training process:

#### [**Introduction**](https://support.cognigy.com/hc/en-us/articles/4417196370834-The-Ultimate-Guide-to-Cognigy-NLU-Training)

#### [**Improving Intent recognition**](https://support.cognigy.com/hc/en-us/articles/4418884124946)

- Machine learning  
- Cognigy Script

#### [**Resolving Intent conflicts**](https://support.cognigy.com/hc/en-us/articles/4418888140562)

- Moving Example Sentences to the better-suited Intent  
- Moving Intents into a hierarchy  
- Merging multiple Intents into one  
- Outsourcing Intents to a separate Flow  
- Adjusting the NLU settings

#### [**Reducing false positives**](https://support.cognigy.com/hc/en-us/articles/4418880928786)

- Machine learning / Reject Intent  
- Adjusting the NLU settings

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