Explore the world of conversational agents in this comprehensive workshop led by Merve Noyan, a Machine Learning Engineer and Google Developer Expert. Gain insights into building your own bot tailored to your specific use case. Delve into frameworks, state-of-the-art natural language understanding, dialogue management, and generative models. Learn about common pitfalls in chatbot development, from training data to production monitoring. Discover the intricacies of intent recognition, named entities, and conversational design. Examine data-driven dialog systems, data augmentation techniques, and methods for handling fallbacks and misclassified intents. Evaluate the pros and cons of generative models and their integration with intent classification. Tackle challenging aspects of chatbot development, including stop words, negations, and multiple intents. Gain valuable insights from real-world examples and compare popular frameworks like RASA and Dialogflow.
Overview
Syllabus
Intro
About me
FAQ Assistance
Personalized Assistance
Use Cases
Personal Experience
Banking bots
Machine learning
What is intended recognition
Bot definition
Intent recognition
Named entities
Dialogue management
Conversational design
Define your problem
Data driven dialog systems
Data augmentation
TFIDF
Embeddings
Handling fallback
Handling misclassified intent
Using generative models
Combining generative models with intent classification
Is generative models good
Feedback mechanism
Examples
trickiest part of working with chatbots
stop words
negations
multiple intents
presentation slides
RAZ vs Dialogflow
Taught by
Abhishek Thakur
