Machine Learning with Python (Coursera)

This course dives into the basics of machine learning using Python. Here, there are several applications of different machine learning models.

Regression

Simple, multiple, polynomial and non-linear regressions.

Classification

KNN, decision trees, logostic regression and SVM.

Clustering

K-means, agglomerative hierarchical clustering (bottom up approach) and density-based.

Recommender systems

Collaborative filtering (based on similar users' preferences) and content-based.

The best classifier

Final project of the course 'Machine Learning with Python'.

In this project, I build a classifier to predict whether a loan case will be paid off or not. I load a historical dataset from previous loan applications, clean the data, and apply different classification algorithm on the data.

Models applied:

• k-Nearest Neighbour

• Decision Tree

• Support Vector Machine

• Logistic Regression

The results are reported as the accuracy of each classifier, using the following metrics when these are applicable:

• Jaccard index

• F1-score

• LogLoass