NLP Techniques for creating AI Chatbots

NLP Techniques for creating AI Chatbots, available at $39.99, has an average rating of 3.35, with 34 lectures, based on 45 reviews, and has 265 subscribers.

You will learn about 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 This course is ideal for individuals who are Anyone that wants to know how chatbots work or Anyone that wants to see how chatbots can be more than basic question responders or Beginner data science students or Anyone that wants to see NLP libraries be applied in real world problems It is particularly useful for Anyone that wants to know how chatbots work or Anyone that wants to see how chatbots can be more than basic question responders or Beginner data science students or Anyone that wants to see NLP libraries be applied in real world problems.

Enroll now: NLP Techniques for creating AI Chatbots

Summary

Title: NLP Techniques for creating AI Chatbots

Price: $39.99

Average Rating: 3.35

Number of Lectures: 34

Number of Published Lectures: 34

Number of Curriculum Items: 34

Number of Published Curriculum Objects: 34

Original Price: $119.99

Quality Status: approved

Status: Live

What You Will Learn

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

Who Should Attend

Anyone that wants to know how chatbots work

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

Beginner data science students

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

Target Audiences

Anyone that wants to know how chatbots work

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

Beginner data science students

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

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 time 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.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Getting Started

Lecture 2: Helpful information

Chapter 2: NLP Fundamentals

Lecture 1: NLP Basics

Lecture 2: Intents

Lecture 3: Entities

Lecture 4: Available resources

Chapter 3: Chatbot Fundamentals

Lecture 1: What are chatbots

Lecture 2: Chatbot examples

Lecture 3: Conversational chatbots

Chapter 4: Starting our chatbot

Lecture 1: Things to always consider

Lecture 2: Proposed bot architecture

Lecture 3: Environment setup

Lecture 4: Environment details

Lecture 5: Base code for client & server

Chapter 5: First intents & entities

Lecture 1: Training a Rasa NLU

Lecture 2: Our Interpreter server & first entities

Chapter 6: Data & Sentence-encoders

Lecture 1: Presenting the Dataset

Lecture 2: Sentence Encoder

Lecture 3: Searching for entities

Lecture 4: A note on pre-trained models

Chapter 7: Constructing the bot actions

Lecture 1: Menu or help

Lecture 2: Filter & help

Lecture 3: Listing and selecting

Lecture 4: Confirm order

Lecture 5: Finalizing

Lecture 6: A note on bot architecture

Chapter 8: Data always more data

Lecture 1: Theory, reasons and caveats

Lecture 2: Auto data generation – Translation to the rescue

Lecture 3: Disambiguation

Lecture 4: Data gathering

Chapter 9: Completing the bot

Lecture 1: Localization

Lecture 2: Speech

Lecture 3: Bonus improvements

Chapter 10: Outro

Lecture 1: Conclusions

Instructors

Popescu Daniel
Machine Learning Engineer

Rating Distribution

1 stars: 4 votes

2 stars: 3 votes

3 stars: 4 votes

4 stars: 14 votes

5 stars: 20 votes

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