https://github.com/anujvyas/Machine-Learning-Projects

This repository consists of all my Machine Learning Projects.
https://github.com/anujvyas/Machine-Learning-Projects

classification clustering deployment google-colab jupyter-notebook machine-learning matplotlib numpy pandas python regression seaborn sklearn

Last synced: about 1 month ago
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This repository consists of all my Machine Learning Projects.

• Host: GitHub
• URL: https://github.com/anujvyas/Machine-Learning-Projects
• Owner: anujvyas
• Created: 2020-03-24T11:18:37.000Z (over 4 years ago)
• Default Branch: master
• Last Pushed: 2023-07-22T12:19:30.000Z (over 1 year ago)
• Last Synced: 2024-10-11T08:21:01.405Z (2 months ago)
• Topics: classification, clustering, deployment, google-colab, jupyter-notebook, machine-learning, matplotlib, numpy, pandas, python, regression, seaborn, sklearn
• Language: Jupyter Notebook
• Homepage:
• Size: 7.36 MB
• Stars: 554
• Watchers: 5
• Forks: 133
• Open Issues: 1
• Metadata Files:
  • Readme: README.md

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• 100-AI-Machine-learning-Deep-learning-Computer-vision-NLP - 👆

README

        
# Machine Learning Projects

![Dataset](https://img.shields.io/badge/Dataset-Kaggle-blue.svg) ![Python 3.6](https://img.shields.io/badge/Python-3.6-brightgreen.svg) ![NLTK](https://img.shields.io/badge/Library-sklearn-orange.svg)

![ML](readme-resources/machine-learning.png)

## Why this repository?

• The main purpose of making this repository is to keep all my Machine Learning projects at one place, hence keeping my GitHub clean!


• It looks good, isn't it?

## Overview

• This repository consists of all my Machine Learning projects.


• Datasets are provided in each of the folders above, and the solution to the problem statements as well.

## Algorithms used

**Regression:**


• _Linear Regression_


• _Multiple-Linear Regression_


• _Logistic Regression_


• _Polynomial Regression_


• _Lasso and Ridge Regression (L1 & L2 Regularization)_


• _Elastic-Net Regression_

**Classification:**


• _K-Nearest Neighbours_


• _Support Vector Machine_


• _Naive Bayes_


• _Decision Tree_


 

**Clustering:**


• _K-Means_


  

**Ensemble:**


• _Random Forest_


• _Adaptive Boosting (AdaBoost)_


• _Extreme Gradient Boosting (XGBoost)_


• _Voting (Hard/Soft)_


**Do ⭐ the repository, if it helped you in anyway.**