"Stay Hungry. Stay Foolish." - Steve Jobs
First of all let me introduce myself. I always had a curious and problem solver attitude and most likely this is the reason I pursued a research career. In the research field is mandatory to have grit, think first then act, and creativity and in my opinion all those characteristics are needed in a successful data scientist.
Due to this and all my previous professional experiences I am deepening my data skills through self learning. I have improved my Python knowledge through a Coursera course and in the last few months I have been improving my machine learning knowledge through online courses and Kaggle challenges.
Therefore, I decided to make this repository public, where you can find the Kaggle's challenges that I have been analyzing since Jan'18.
Ok! Let's fast-forward to the list of Codility's problems and Kaggle's challenges that I have analyzed:
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Codility's Problems - proposes possible solutions to Codility's challenges with different levels of difficulty
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Titanic Exploration - like any data scientist this was my first Kaggle challenge and in this notebook I did feature engineering around raw titanic data;
(Available Soon)
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Flight Delays and Cancellations - is a Kaggle challenge where the goal is to predict when a flight is delayed. The goal was to go through all data science steps: basic statistics, baseline, data exploration / understanding, feature engineering and model iteration.
Let me know your thoughts regarding what I'm doing and I am available to discuss any question that you possible have.
Inês Rosete | June 2018