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

    Jupyter Notebook

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

    Jupyter Notebook

  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 67 67

  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 23 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 35 4

1,062 contributions in the last year

Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Mon Wed Fri

Contribution activity

August 2019

17 contributions in private repositories Aug 1 – Aug 21

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