Data Science Portfolio

This portfolio is a compilation of notebooks which I created for data analysis or for exploration of machine learning algorithms. A separate category is for separate projects.

Machine learning projects.

California Housing prices

In this project I am trying to predict the housing prices in California using features like the age of the house or its proximity to the ocean. For this project I used a simple linear regression and the XGboost method.

the code can be found here.

Minimizing the Churn Rate Through Analysis of Financial Habits

Using classification techniques, the main purpose of this project is to create an algorithm that could predict if a customer it’s going to churn a subscription product. In this way, the company will adquire knoledge about which products should improve or offer to minimize this churn rate.

the code can be found here.

Exploratory Data Analysis.

Accidents in UK

With the information from the accidents in UK during the period 2004-2014, the objective of this project is to know more about the characteristics of the accidents in the roads. The dataset is divided in three databases(vehicles,accidents and casualties involved)

the code can be found here.

Deep learning projects

Credit card fraud detector

Manipulating a database of 300.000 transactions made with a credit card, the objective of this project is to create a deep neural network that classify the transactions in fraudulent or normal transaction.

the code can be found here.