├── Final Project.ipynb
├── README.md
└── certificate.pdf


/README.md:
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 1 | # IBM-final-project-Machine-Learning
 2 | Final project of IBM's course https://www.coursera.org/learn/machine-learning-with-python on coursera
 3 | 
 4 | A simple comparison between KNN,SVM,Decision Tree and Logistic Regression models on a given data set of loans records.
 5 | final results:
 6 | 
 7 | 
 8 | | Algorithm          | Jaccard | F1-score | LogLoss |
 9 | |--------------------|---------|----------|---------|
10 | | KNN                | 0.7407  | 0.7144   | NA      |
11 | | Decision Tree      | 0.7592  | 0.7618   | NA      |
12 | | SVM                | 0.7592  | 0.6959   | NA      |
13 | | LogisticRegression | 0.7777  | 0.7089   | 0.4947  |
14 | 
15 | 
16 | Please read the note book for information about the data and implementation of classifiers used.
17 | 
18 | *Please note that results may be improved by engineering new features or using different hyper parameters ,I have tried just to create a simple prediction only for demonstrating use of different classifiers from scikit learn library .*
19 | 


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/certificate.pdf:
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https://raw.githubusercontent.com/Moeinh77/IBM-final-project-Machine-Learning/b99f24a053235f59537a851307402f3e1777b771/certificate.pdf


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