Titanic database study

In this project, the study of the Titanic database was carried out, where the project will be divided into three:

• First part: we are going to work on some of the most important aspects of the knowledge discovery from data (KDD) process: data storage and loading, exploratory data analysis, data preprocessing, model validation.

• Second part: we will study the most used models in scikit-learn to know the different hyperparameters that configure them and to study the resulting classifiers. In addition, we will see model selection methods oriented to obtain an optimal configuration of hyperparameters.

• Third part: In this practice we will work with models based on neural networks using the tensorflow library.

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