• Deeplearning Path

May 2019

Natural Language Processing

Rasa ChatBot integration with Slack and Facebook Messenger

This article will guide people to integrate Rasa ChatBot with Slack and Facebook Messenger. First we will see how the integrated platforms will connect to the rasa’s chatbot server. Please see the following overview chart. The diagram above seems quite confusing, I will explain now. First, the integrated platform will Read more…

By Pham Hung, 4 years4 years ago
Natural Language Processing

Rasa NLU in Depth: Part 2 — Entity Recognition

Welcome back to part 2 of the Rasa NLU in Depth series. In this three-piece blog post series we share our best practices and experiences about Rasa NLU which we gained in our work with community and customers all over the world Understanding the user’s intent is only part of Read more…

By duyanh, 4 years4 years ago
Natural Language Processing

Rasa NLU in Depth: Part 1 — Intent Classification

AI assistants have to fulfill two tasks: understanding the user and giving the correct responses. The Rasa Stack tackles these tasks with the natural language understanding component Rasa NLU and the dialogue management component Rasa Core. Based on our work with the Rasa community and customers from all over the Read more…

By duyanh, 4 years4 years ago
Natural Language Processing

Conversational AI: Your Guide to Five Levels of AI Assistants in Enterprise (from rasa blog)

I wanted to give a bit more detail to the concept of five levels of AI assistants. This is our way of quantifying the path that AI assistants have been following, and will travel over the coming years. This is your guide to understanding the path to true conversational AI. Read more…

By duyanh, 4 years4 years ago
Natural Language Processing

Recurrent Neural Networks — Part 2

RNN if you look up the definition of the word Recurrent, you will find that it simply means occurring often or repeatedly. So why are these networks called Recurrent Neural Networks? It’s simply because with RNN’s, we perform the same task for each element in the input sequence. RNN’s also Read more…

By duyanh, 4 years4 years ago
Natural Language Processing

Recurrent Neural Networks — Part 1

The neural network architectures such as multi-layers perceptron (MLP) were trained using the current inputs only. We did not consider previous inputs when generating the current output. In other words, our systems did not have any memory elements. RNNs address this very basic and important issue by using memory (i.e. past inputs to the Read more…

By duyanh, 4 years4 years ago
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