NLP – Building your own chatbots using AI
NLP – Building your own chatbots using AI, available at $44.99, has an average rating of 4.42, with 33 lectures, based on 64 reviews, and has 5286 subscribers.
You will learn about Fundamentals of chatbot design Understanding the concepts of NLP Implementation of Rule based chatbot Implementation of NLP based self learning bot This course is ideal for individuals who are Anyone who wants to build his/her own chatbot It is particularly useful for Anyone who wants to build his/her own chatbot.
Enroll now: NLP – Building your own chatbots using AI
Summary
Title: NLP – Building your own chatbots using AI
Price: $44.99
Average Rating: 4.42
Number of Lectures: 33
Number of Published Lectures: 33
Number of Curriculum Items: 33
Number of Published Curriculum Objects: 33
Original Price: ₹999
Quality Status: approved
Status: Live
What You Will Learn
- Fundamentals of chatbot design
- Understanding the concepts of NLP
- Implementation of Rule based chatbot
- Implementation of NLP based self learning bot
Who Should Attend
- Anyone who wants to build his/her own chatbot
Target Audiences
- Anyone who wants to build his/her own chatbot
Welcome! Anyone interested in learning how to build their own chatbots using natural language processing (NLP) methods should take this course. The fundamentals of NLP and how chatbot creation uses it will be covered.
You will acquire practical experience during the course creating your own chatbot using well-known NLP libraries and frameworks like NLTK. You’ll discover how to use intents, entities, and action to train your model.
Additionally, you will discover the various varieties of chatbots, including rule-based, retrieval-based, and generative ones. You will also discover how chatbots are evaluated.
A chatbotis a computer program designed to simulate conversation with human users, especially over the Internet. They can be integrated into various platforms such as websites, mobile apps, messaging apps, and more. They are commonly used for customer service, providing information, or automating repetitive tasks.
Natural Language Processing (NLP) is a subfield of artificial intelligence that focuses on the interaction between computers and humans in natural language. It involves using techniques from computer science, artificial intelligence, and linguistics to process, analyze, and generate human language. NLP tasks include speech recognition, natural language understanding, sentiment analysis, text summarization, machine translation, and more. NLP techniques are used in many applications such as chatbots, virtual assistants, and language translation software.
These are the contents of this course
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Fundamentals of Chatbots
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Types of chatbots – Rule based, AI based
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Fundamentals of NLP
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NLP Techniques – Stemming, Lemmatization, Bag of Words, TF-IDF, Cosine Similarity
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Rule based chatbots – Implementation
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NLP Wordnet – Implementation
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NLP Incorporated chatbots – Implementation
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Dynamic Web Surfing Chatbots – Implementation
Projects:
1. Building a rule based chatbot
2. Building an NLP based chatbot
3. Building a dynamic web surfing chatbot
Course Curriculum
Chapter 1: Introduction
Lecture 1: Introduction
Lecture 2: 2. Basics of Chatbots and conversation
Chapter 2: Concepts, Types and Modes of Chatbots
Lecture 1: Info
Lecture 2: 3. Types of chatbots
Lecture 3: 4.Rule Based chatbots
Lecture 4: 5. Implementation – Rule Based chatbots
Lecture 5: 6. NLP Based chatbots
Lecture 6: 7. Different modes of chatbots
Chapter 3: Concepts of Natural Language Processing and its Toolkit
Lecture 1: 8. Introduction to Natural Language Processing
Lecture 2: 9. Breaking down NLP Terms
Lecture 3: 10. Introduction to nltk
Lecture 4: 11. Working with nltk wordnet
Lecture 5: 12.Applications of Natural Language Processing
Chapter 4: Steps in developing a NLP based Chatbot
Lecture 1: 13. Steps in building a NLP Chatbot
Lecture 2: 14. Data Preprocessing steps in NLP – I
Lecture 3: 15. Stemming and Lemmatization – II
Lecture 4: 16. The TF-IDF Vectorizer
Lecture 5: 17. Solving TF-IDF for an example
Lecture 6: 18. The Cosine Similarity
Chapter 5: Project – Implementation of an NLP based Chatbot
Lecture 1: 19. Implementation – Tokenization
Lecture 2: 20. Implementation – Lemmatization
Lecture 3: 21. Implementation – Greeting
Lecture 4: 22. Implementation – Generating response
Lecture 5: 23. Bot in Action!
Chapter 6: Dynamic API + NLP Bots!
Lecture 1: 24. Dynamic web surfing bot
Lecture 2: Bonus Lecture
Chapter 7: AI Based Chatbots
Lecture 1: Introduction to AI Based Chatbots
Lecture 2: Neural Networks are Function Approximators
Lecture 3: A simple FCNN – Lot more to come!
Lecture 4: Why not simple FCNs for NLP Applications?
Lecture 5: Understanding the architecture of Recurrent Neural Networks
Chapter 8: AI Based Chatbot – Implementation
Lecture 1: Implementing a RNN Based Chatbot in Tensorflow from Scratch [1 hour]
Lecture 2: Bonus Lecture
Instructors
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Sujithkumar MA
Engineer | Course Instructor -
Harini S
AR Course Instructor
Rating Distribution
- 1 stars: 1 votes
- 2 stars: 3 votes
- 3 stars: 10 votes
- 4 stars: 23 votes
- 5 stars: 27 votes
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