What are and how chatbots work

Different types of chatbots

How to architect a chatbot

Natural Language Processing Tecchniques

How to classify intents

Named Entity Recognition

NLP Fundamentals

Similarity detection using Embeddings and Sentence-encoders

How to do disambiguation

Auto generation of training data

Localization (using translation)

Speech recognition

Speech synthesization

Build complex chatbots that go past the basic functionalities

Be familiar with Python

Linux experience is helpful but not mandatory

In the past few years Chatbots have become a must-have for businesses and companies. With latest advancements in Natural Language Processing we can build better chatbots in a fraction of the it took a few years ago.

As such, many solutions like DialogFlow, Wit, and chatbot frameworks emerged that offer a quick way to create basic chatbots. But they have limitations, especially if you want to make something more complex and personalized. Because of that, I'm showing you how to use state-of-the-art NLP libraries and combine them to get a more advanced possible use of a chatbot.

After this course, the amazing thing won't be that the chatbot responds, but the entire process you're able to create and the possibilities that become available. You'll be more confident in tackling more difficult problems and will be able to make a more complex chatbot that offers more variety and functionality.

Anyone that wants to know how chatbots work

Anyone that wants to see how chatbots can be more than basic question responders

Bner data science students

Anyone that wants to see NLP libraries be applied in real world problems



DOWNLOAD
uploadgig


rapidgator


nitroflare