28utkarsh / Basic-Algorithms-of-Machine-Learning

Implementation of Machine Learning Algorithms using Python Libraries

Basic Machine Learning Algorithms

This repository contains basic Machine Learning algorithms implementation in both Python and R. The algorithms are as follows:

Supervised Algorithms

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1. Decision Tree Classification
2. Decision Tree Regression
3. Kernel SVM
4. K-Nearest Neightbors
5. Logistic Regression
6. Multiple Linear Regression
7. Naive Bayes
8. Polynomial Regression
9. Random Forest Classification
10. Random Forest Regression
11. Simple Linear Regression
12. Support Vector Machine Classification
13. Support Vector Regression

Unsupervised Algorithms

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1. K-Means Clustering
2. Hierarchical Clustering

Execution

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Python and R scripts are provided for every algorithm.

Python

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To run the python script run the following command.

# Go to the Models Directory
cd "Decision Tree Classification"

# Run the corresponding python script
python3 decision_tree.py

R

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Load the R script in R studio and simply run the file.

References

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1. The code and the datsets belong to the Machine Learning Course at Udemy.