Machine Learning Stories

Welcome to the Machine Learning Stories repository! This repository contains code samples and Jupyter notebooks demonstrating various machine learning techniques and algorithms, along with stories and explanations for each method.

ML Algorithms

Here we will explore 2 types of Machine Learning algorithm examples:

1. Supervised Learning

   • A. Regression
     • Linear Regression
     • Ridge Regression
     • Lasso Regression
     • Support Vector Regression (SVR)
     • Decision Trees Regression
     • Random Forest Regression
     • Gradient Boosting Regression
     • Neural Networks Regression
   • B. Classification
     • Logistic Regression
     • Support Vector Machines (SVM)
     • k-Nearest Neighbors (KNN)
     • Naive Bayes
     • Decision Trees
     • Random Forest
     • Gradient Boosting (e.g., XGBoost, LightGBM, CatBoost)
     • Neural Networks (e.g., Multilayer Perceptron)

2. Unsupervised Learning

   • Clustering
     • K-Means Clustering
     • Hierarchical Clustering

Getting Started

To get started with the examples in this repository, follow these steps:

1. Clone the repository:

   git clone https://github.com/DataByteSun/Machine-Learning.git
   

Technologies Used

• Programming Language: Python
• Tools: Jupyter Notebook