Practical Chatbots
Improving Business Processes Using ML-Based Chatbots
I developed a process and app for creating and deploying chatbots for support and question answering purposes for Novetta. This solution focused on practicality including minimizing the dataset needed, minimizing training/retraining needed, eliminating the need to retrain if policies change, and empowering domain experts to expand and improve the responses of without requiring a ML engineer for every tweak.
This approach was built on the sentence transformer (siamese BERT) architecture and the core machine learning technology was semantic similarity. I built it using dash, but any deployment method could be used (slack bot, email bot, web app, etc.)
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