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

Machine Learning example includes code, explanations, and insights into the story behind the problem being solved.
https://github.com/databytesun/machine-learning

artificial-intelligence computer-vision data-science exploratory-data-analysis linear-regression machine-learning machine-learning-beginners machine-learning-courses machine-learning-practice machine-learning-projects machine-learning-stories python regression-models

Last synced: 10 months ago
JSON representation

Machine Learning example includes code, explanations, and insights into the story behind the problem being solved.

• Host: GitHub
• URL: https://github.com/databytesun/machine-learning
• Owner: DataByteSun
• Created: 2024-09-19T08:25:36.000Z (over 1 year ago)
• Default Branch: master
• Last Pushed: 2025-02-23T13:30:05.000Z (10 months ago)
• Last Synced: 2025-02-23T14:26:18.569Z (10 months ago)
• Topics: artificial-intelligence, computer-vision, data-science, exploratory-data-analysis, linear-regression, machine-learning, machine-learning-beginners, machine-learning-courses, machine-learning-practice, machine-learning-projects, machine-learning-stories, python, regression-models
• Language: Jupyter Notebook
• Homepage:
• Size: 7.34 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

          
# 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](Regression/README.md)

      - [Linear Regression](Regression/Notebooks/Multiple_Linear_regression.ipynb)

      - Ridge Regression

      - [Lasso Regression](Regression/Notebooks/Lasso_Regression.ipynb)

      - Support Vector Regression (SVR)

      - Decision Trees Regression

      - Random Forest Regression

      - Gradient Boosting Regression

      - Neural Networks Regression

   - B. [Classification](Classification/README.md)

      - Logistic Regression

      - Support Vector Machines (SVM)

      - k-Nearest Neighbors (KNN)

      - Naive Bayes

      - [Decision Trees](Classification/Notebooks/Decision_Tree.ipynb)

      - [Random Forest](Classification/Notebooks/Random_Forest_Tree.ipynb)

      - 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:

   ```bash

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

## Technologies Used

- **Programming Language:** Python

- **Tools:** Jupyter Notebook