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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. Predicting PM25 pollution in Hyderabad using flask and SqlAlchemy: Using Flask, PostgreSQL, GitHub Actions and ElephantDB to make predictions using an ML model, store and extract these predictions, and display on a web app. (Blog posts 1, 2, 3)
  2. 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.
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