nlddfn / projects

List of personal projects published on Github

Projects

In this folder I listed the projects I have been recently working on:

1. Better Life Index across OECD countries: a critical perspective: Can we measure the well-being of a society? How does that compare to our personal perception? While a better understanding of people’s well-being is important to developing better policies, merging measured data and the individual experience in one coherent picture, remains challenging. In this project, we will try to describe this problem, by exploring the so called Better Life Index.

2. Tracking migration patterns through Eastern and Southern Europe with Shiny: This project attempts to visualize the migration patterns followed by over a million migrants in the last 18 months, by means of an interactive map developed in "Shiny". While offering a dynamic picture of the migration flow through Eastern Europe, from Greece through the Balkans, up to Austria, the project aims at analyzing its composition, in terms of country of origin and gender.

3. Landing my dream job by scraping Glassdoor.com: In this post I am going to use web scraping to define a simple recommendation system for data scientists looking for new employment. The idea is using to use the resources published on Glassdoor.com to create a dataset addressing the US job market for data scientists and data analysts. A web application developed in R- Shiny, allows the user to upload a resumé and receive a list of recommended job posts, depending on the candidate skills, education and work experience.

4. Predicting Higgs Boson Signal: The Higgs boson was the last hold-out particle remaining hidden during the quest to check the accuracy of the Standard Model of Physics. After decades of search, on March 14, 2013 CERN officially announced the confirmation of the Higgs boson. This Kaggle competition is about building a machine learning algorithm to filter out signal from background noise using selected & simulated ATLAS experiment data.

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6. Trivago BI challenge: This mini project focuses on predicting the number of clicks expected for a given hotel, as a function of location, average price, competitivity (offering a cheaper rate for the same hotel with respect to competitors) and ranking on Trivago's website.

7. Bonobos challenge: For a retail company, the goal is to maximize the relevance of each interaction a customer has with the brand. We can use data to contribute to this effort by generating personalized content for customers, for example in the form of outfit recommendations.