/Machine-Learning

This repository showcases my machine learning projects built on top of SK-learn. Various algorithms, ensemble methods, bagging, boosting, stacking, regression algo etc were implemented.

Primary LanguageJupyter Notebook

Machine-Learning



This repository contains all important widely used machine learning algorithms implemented in various projects.


1. Diabetes prediction

This dataset contains a diabetes prediction model built by using various ML algorithms like Logistic Regression, Support Vector Classifier, Decision Tree, Random Forest.

2. Digit prediction

Here image recognition is performed by using famous handwritten digits dataset called MNIST.

3. Species prediction

This project uses Naive Bayes algorithm to predict species of Iris Dataset.

4. Car evaluation

Car evaluation is performed by building ML models using following algorithms: Logistic Regression, Support Vector Classifier, Decision Tree, Random Forest, Naive Bayes, Gradient Boost, XGboost

5. Life expectancy

A regression project.

6. Naive Bayes

Contains practical implementation of Naive Bayes.