Machine Learning Practice

This repository showcases my foundational knowledge in machine learning concepts, based from the Machine Learning series by TechWithTim. It serves as my requirement for aspiring members of the PUP Hygears Programming Team, demonstrating my ability to apply theoretical knowledge to practical implementations.

Linear Regression Algorithm

• Description: Linear regression is a fundamental supervised learning algorithm used for modeling the relationship between a dependent variable and one or more independent variables.
• File Name: linearRegression.py
• Dataset: student-mat.csv
• Dataset Source: UCI's Machine Learning Repository

K-Nearest Neighbor Algorithm

• Description: Support Vector Machines (SVM) are powerful supervised learning models used for classification and regression tasks.
• File Name: knn.py
• Dataset: car.data
• Dataset Source: UCI's Machine Learning Repository

Support Vector Machine Algorithm

• Description: Support Vector Machines (SVM) are powerful supervised learning models used for classification and regression tasks.
• File Name: svm.py
• Dataset: Built-in sklearn dataset

K-Means Clustering Algorithm

• Description: K-means clustering is an unsupervised learning algorithm used for partitioning data into distinct clusters based on similarity.
• File Name: kmc.py

Prerequisites

python

pip install pandas

tensorflow

pip install tensorflow

numpy

pip install numpy

pandas

pip install pandas

scikit-learn

pip install scikit-learn

Contributor

Erosa, Marvin James A.

• Dataset: Built-in sklearn dataset