In this presentation, I explain the steps for data cleaning and modelling for an use case related to Banking domain.

In this presentation, I present the analysis and the results of the previous notebook. The use case is related to a mobile application and the introduction of new features.

We are developing and managing our fitness mobile application. Each new feature should be carefully developed and tested. Let’s image we want to test the impact on the loading time of a new feature and we have just 24h to test it.

In this second part of the analysis, we will apply some machine learning techniques to predict the performances of the football players.

In this project, we will try to predict the performances of the players of Italian football championship Serie A. The project is meant in the context of Fantasy Football, a popular game in which a group of friends organize a virtual team of real serie A players. The aim of the game is to score more than the opponen (the score is the sum of the performance evaluation marks) of the players of your team. Predicting the marks of your players could definitely be an advantage for a fantasy football coach.

Now available a brief and clear presentation based on the data analysis and the take-aways: get the PDF

In this first data analysis, I will have fun analyzing the data from a quiz game. However, we will have access just to collection of the user feedbacks related to the questions.

This space is meant to be my Data Analysis portfolio. In the last month I have been less busy with the PhD stuffs. For this reason I decided to dive into data analysis in order to:

• play with state of the art data analysis and machine learning libraries
• have fun, trying to answer some of the questions I have been asking myself in the last years
• a little bit of show-off of my capacities and, above all, my creativity!