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Websites and deployments

This blog lists the ML apps and websites that I have built and are publicly accessible.

Python ML deployments

  1. Enterprise AI chatbot: A financial question-answering application that answers user queries based on documents, databases and news.
  2. Predicting PM25 pollution in Hyderabad using flask and SqlAlchemy: Using Flask, PostgreSQL, GitHub Actions and Neon DB to make predictions using an ML model, store and extract these predictions, and display on a web app. (Blog posts 1, 2, 3)
  3. Streamlit for deployment: Using Streamlit to deploy simple data science models and insights. (Project: Bid allocation model)

Project-specific POC's

  1. OC And Gym Dashboard: Churn dashboard showing the effect of different decisions that the business can take.
  2. Contest Insights Dashboard: Dashboard for allocating different contests as part of a company's Rewards programme. (Project IIMB Project)

RShiny Dashboards

  1. T-test: Demonstrating t-test using simulated data.
  2. Anova simulation: Demonstrating Anova three-class F-test.
  3. Linear Programming: Demonstrating the solution for a linear minimisation programme (blog post)
  4. Machine Learning: Demonstrating the concepts of experience, task and performance in ML.

Student deployments

These are apps that my students or mentees have deployed and maintain.
1. Predictive maintainence of aircraft engines
2. IBM Licensing Asistant
3. Stock analyser - US Stocks
4. Enterprise Chatbots by students: 1, 2, 3, 4, 5

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