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  1. A case study on predicting customer churn using machine learning.

    Jupyter Notebook 2

  2. Use machine learning (NLP) to demonstrate whether Federal Funds rate changes can be accurately predicted using just the FOMC - the US Federal Reserve Bank - meetings minutes.

    Jupyter Notebook 7 3

  3. This is my personal website. I built it in Ruby on Rails with Haml and other tools. Includes: portfolio section, resume, speaking, and blog with the most recent blog post on the home page. It's ope…

    Ruby 64 66

  4. A mini project to play around with World Bank data in JSON format.

    Jupyter Notebook

  5. An app I created so developers can track the info they need: now includes Twitter API feeds and Machine Learning, Python, and Ruby on Rails sections.

    Ruby 22 8

  6. An app to find developers in a specific city based on their programming language. Built in Angular 4 using Angular CLI, TypeScript, Node.js, and of course Javascript.

    TypeScript 33 6

156 contributions in the last year

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Contribution activity

October 2021

5 contributions in private repositories Oct 3 – Oct 25

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