A project inspired by the COVID-19 pandemic. It aims to compare the effectiveness of the measures taken by different countries to fight the virus. The different visuals help in showing the effectiveness of one measure through time and aids in comparing several countries at the same time.
A Kaggle competition where we use several machine learning models to predict who will survive on the titanic based on their age, gender, ticket price and other factors. The submission has a public score of 0.76 (Top 25%). The methods used are exploratory where we apply different types of machine learning models: (Tree Classifier, Adabooost, neural networks, genetic algorithims). In addition to that feature engineering is used to select the most useful features. The current accuracy of the model is around 87%.
In this project, we analyze data obtained from a twitter account called ‘WerateDogs’ which rates dogs on a scale of 10 (usually in a very absurd way).
For this project, we work on understanding the results of an A/B test run by an e-commerce website. The goal is to work through the notebook to help the company understand if they should implement a new page, keep the old page, or perhaps run the experiment longer to make their decision.
The report aims firstly to investigate the Brazilian health care system and to find a number of factors that can lead to the patient not showing for an appointment. For that, the questions to be answered are as follows: