Files Included :
01 - Building an AI chatbot (3.75 MB)
02 - Getting the most out of this course (2.81 MB)
03 - Version check (1.78 MB)
01 - Overview of chatbot technologies and trends (5.29 MB)
02 - Fundamentals of chatbots (12.55 MB)
03 - Introduction to Hugging Face (6.17 MB)
04 - Demo Exploring Hugging Face (20.72 MB)
05 - Designing a chatbot for customer experience (9.23 MB)
06 - Demo Implementing the chatbot in Python (31.96 MB)
07 - Solution Build a basic chatbot (13.15 MB)
01 - Introduction to OpenOrca dataset (6.7 MB)
02 - Demo Building a chatbot with OpenOrca (15.72 MB)
03 - Further enhancing chatbot features (11.26 MB)
04 - Solution Enhance the chatbot with OpenOrca (40.31 MB)
01 - Principles of model pruning (9.08 MB)
02 - Demo Pruning the chatbot model (24.61 MB)
03 - Theory and practice of model distillation (15.66 MB)
04 - Demo Applying model distillation to the chatbot (23.28 MB)
05 - Understanding and implementing quantization (11.65 MB)
06 - Demo Quantizing the chatbot model (17.52 MB)
07 - Demo Overview of the results (33.32 MB)
08 - Solution Prepare the chatbot for deployment (33.2 MB)
01 - Introduction to Gradio (10.94 MB)
02 - Deploying the chatbot to Hugging Face Spaces (8.51 MB)
03 - Demo Deploying to Hugging Face Spaces (28.82 MB)
04 - Details to consider on deploying to Hugging Face Spaces (11.04 MB)
01 - How to deploy to ECS (16.17 MB)
02 - Demo Creating the Dockerfile (11.64 MB)
03 - Demo Writing a Terraform file for AWS ECS deployment (14.41 MB)
04 - Demo Deploying the Dockerized chatbot to AWS ECS (14.11 MB)
01 - Metrics and benchmarks for chatbot performance (8.85 MB)
02 - Demo benchmarking our chatbot (20.54 MB)
03 - Analyzing and improving your chatbot (4.51 MB)
01 - Recap of key learnings and tips (3.25 MB)
02 - Continuing on with AI chatbots (4.54 MB)
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