AI Workshop: Advanced Chatbot Development
3h 18mAdvanced2024-09-03
Authors
Axel Sirota
Course details
Businesses increasingly rely on AI-driven solutions to enhance customer interactions, streamline services, and stay competitive. In this rapidly evolving digital landscape, the ability to build and deploy sophisticated chatbots is crucial. This hands-on course empowers data scientists and ML engineers to leverage these cutting-edge tools and techniques, ensuring their organizations lead in delivering exceptional customer experiences.
Instructor Axel Sirota guides you in mastering the development and deployment of advanced chatbots and LLMs. Key objectives include understanding chatbot technologies and trends, using Hugging Face for development, and implementing chatbots with the OpenOrca dataset. Along the way, Axel covers advanced techniques to optimize performance and efficiency and provides hands-on experience deploying chatbots to Hugging Face Spaces with Gradio and to AWS ECS using Docker and Terraform.
Prerequisites
Familiarity with Python programming, as it's the primary language used in the course
Some experience with machine learning concepts and methodologies
Prior exposure to TensorFlow and Keras for model building and training
Basic knowledge of AI and natural language processing (NLP) techniques
Instructor Axel Sirota guides you in mastering the development and deployment of advanced chatbots and LLMs. Key objectives include understanding chatbot technologies and trends, using Hugging Face for development, and implementing chatbots with the OpenOrca dataset. Along the way, Axel covers advanced techniques to optimize performance and efficiency and provides hands-on experience deploying chatbots to Hugging Face Spaces with Gradio and to AWS ECS using Docker and Terraform.
Prerequisites
Familiarity with Python programming, as it's the primary language used in the course
Some experience with machine learning concepts and methodologies
Prior exposure to TensorFlow and Keras for model building and training
Basic knowledge of AI and natural language processing (NLP) techniques
Skills covered
Hugging FaceNatural Language Processing (NLP)Amazon Web Services (AWS)AmazonGenerative AIArtificial Intelligence (AI)One-Off
Concepts
0. Introduction
- 01 - Building an AI chatbot
- 02 - Getting the most out of this course
- 03 - Version check
1. Understanding Chatbots and Hugging Face
- 04 - Overview of chatbot technologies and trends
- 05 - Fundamentals of chatbots
- 06 - Introduction to Hugging Face
- 07 - Demo - Exploring Hugging Face
- 08 - Designing a chatbot for customer experience
- 09 - Demo - Implementing the chatbot in Python
- 10 - Solution - Build a basic chatbot
2. Building an Advanced Chatbot with OpenOrca
- 11 - Introduction to OpenOrca dataset
- 12 - Demo - Building a chatbot with OpenOrca
- 13 - Further enhancing chatbot features
- 14 - Solution - Enhance the chatbot with OpenOrca
3. Preparing Model for Deployment
- 15 - Principles of model pruning
- 16 - Demo - Pruning the chatbot model
- 17 - Theory and practice of model distillation
- 18 - Demo - Applying model distillation to the chatbot
- 19 - Understanding and implementing quantization
- 20 - Demo - Quantizing the chatbot model
- 21 - Demo - Overview of the results
- 22 - Solution - Prepare the chatbot for deployment
4. Deploying to Hugging Face Spaces with Gradio
- 23 - Introduction to Gradio
- 24 - Deploying the chatbot to Hugging Face Spaces
- 25 - Demo - Deploying to Hugging Face Spaces
- 26 - Details to consider on deploying to Hugging Face Spaces
5. Deploying to AWS ECS Using Terraform
- 27 - How to deploy to ECS
- 28 - Demo - Creating the Dockerfile
- 29 - Demo - Writing a Terraform file for AWS ECS deployment
- 30 - Demo - Deploying the Dockerized chatbot to AWS ECS
6. Evaluating Chatbot Performance
- 31 - Metrics and benchmarks for chatbot performance
- 32 - Demo - benchmarking our chatbot
- 33 - Analyzing and improving your chatbot
Conclusion
- 34 - Recap of key learnings and tips
- 35 - Continuing on with AI chatbots