ML-Practice

In this repository, I share how to code common machine learning algorithms using low level libraries.

Demonstrating these algorithms usually requires data so I included links to them in the header of each script that requires it.

Name		Name	Last commit message	Last commit date
Latest commit History 17 Commits
01 Linear Regression One Variable		01 Linear Regression One Variable
02 Linear Regression Multiple Variables		02 Linear Regression Multiple Variables
03 Polynomial Regression		03 Polynomial Regression
04 Normal Equation		04 Normal Equation
05 Logistic Regression		05 Logistic Regression
06 Logistic Regression Multiple Classes		06 Logistic Regression Multiple Classes
07 Regularization		07 Regularization
08 Support Vector Machine Linear Kernel		08 Support Vector Machine Linear Kernel
09 Support Vector Machine Gaussian Kernel		09 Support Vector Machine Gaussian Kernel
10 K-Means Clustering		10 K-Means Clustering
11 Principal Component Analysis		11 Principal Component Analysis
12 Anomaly Detection		12 Anomaly Detection
.gitignore		.gitignore
LICENSE		LICENSE
README.md		README.md

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