This is the final project of the course Machine learning with Python by IBM on coursera :- https://www.coursera.org/learn/machine-learning-with-python
You load a historical dataset from previous loan applications, clean the data, and apply different classification algorithm on the data.The data csv file is provided in final lab file. You are expected to use the following algorithms to build your models:
- k-Nearest Neighbour
- Decision Tree
- Support Vector Machine
- Logistic Regression
The results is reported as the accuracy of each classifier, using the following metrics when these are applicable:
- Jaccard index
- F1-score
- LogLoass
And the final result should look like this :
