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https://github.com/geraked/machine-learning

Implementation of Machine Learning Algorithms From Scratch
https://github.com/geraked/machine-learning

ai amirkabir-university artificial-intelligence ce5501 classification clustering computer-engineering computer-science data-science geraked machine-learning machine-learning-algorithms machine-learning-from-scratch ml ml-from-scratch outlier-detection rabist regression

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Implementation of Machine Learning Algorithms From Scratch

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# Machine Learning

Implementation of Some of the Machine Learning (ML) Algorithms From Scratch in Python

## Homework 1

[Problems](hw1/problem.pdf) | [Solutions (Report)](hw1/report.pdf)

- Data Visualization ([Source code](hw1/src/P2.ipynb))
- Univariate Polynomial Regression using Gradient Descent and Normal Equation ([Source code](hw1/src/P3.ipynb))
- Multivariate Polynomial Regression, Stepwise Feature Selection (Backward Elimination), Cook's Distance and DFFITS plots from scratch. Fixing Heteroscedasticity and Multicollinearity. ([Source code](hw1/src/P4.ipynb))

## Homework 2

[Problems](hw2/problem.pdf) | [Solutions (Report)](hw2/report.pdf)

- Decision Tree ([Source code](hw2/src/P3.ipynb))
- Ensemble Learning - Bagging algorithm using Decision Tree (Random Forest) ([Source code](hw2/src/P2.ipynb))
- KNN using Euclidean and Cosine distance, Confusion Matrix for Multi-class Classification, Optical Recognition of Handwritten Digits ([Source code](hw2/src/P4.ipynb))

## Homework 3

[Problems](hw3/problem.pdf) | [Solutions (Report)](hw3/report.pdf)

- Implementation of Naive Bayes Algorithm for Spam Email Detection ([Source code](hw3/src/P3.ipynb))

## Homework 4

[Problems](hw4/problem.pdf) | [Solutions (Report)](hw4/report.pdf)

- Custom kernels for Support Vector Machine (SVM) ([Source code](hw4/src/P2.ipynb))

## Homework 5

[Problems](hw5/problem.pdf) | [Solutions (Report)](hw5/report.pdf)

- K-means clustering, Outlier detection ([Source code](hw5/src/P2.ipynb))
- DBSCAN, Evaluation Metrics (Accuracy, Entropy, Purity) ([Source code](hw5/src/P3.ipynb))
- Q-learning through Epsilon-Greedy Algorithm ([Source code](hw5/src/P4.ipynb))

## Final Project

[Problems](final-project/problem.pdf) | [Solutions (Report)](final-project/report.pdf)

- Multi-output Regression ([Source code](final-project/src/P1.ipynb))
- Skin Detection ([Source code](final-project/src/P2.ipynb))
- Credit Approval ([Source code](final-project/src/P3.ipynb))

## Author

**Rabist** - view on [LinkedIn](https://www.linkedin.com/in/rabist)

## Details

- **Course:** Machine Learning (CE5501) - MS
- **Teacher:** [Dr. Ehsan Nazerfard](https://aut.ac.ir/cv/2384/EHSAN-NAZERFARD?slc_lang=en)
- **Univ:** Amirkabir University of Technology
- **Semester:** Fall 2022

## License

Licensed under [MIT](LICENSE).