profit estimation of companies with linear regression

In this Project we build fingerprint matching system that leverages a Siamese network to achieve accurate and efficient Fingerprint identification. The system consists of three main stages: image preprocessing, feature extraction, and matching.

Data preparation, statistical reasoning and machine learning are used to solve an unbalanced classification problem. Different techniques are employed to train and evaluate models with unbalanced classes.

This repository contains all the Machine Learning projects I did using different Machine Learning methods. Python being the main software used.

Personality Recognition from text using nlp techniques

A Diabetics Prediction website

Linear Regression Practise

Run three different classification algorithms for explaining whether region's economies grew by more than 5% based on the data provided. Standard goodness measures for classification algorithms also included.

Comparative Analysis of Decision Tree Algorithms in Number Classification: Bagging vs. Random Forest vs. Gradient Boosting Decision Tree Classifiers

3 modelos de classificação para analisar churn de um empresa de telecom e ao final responder a pergunta: Qual modelo teve o melhor desempenho?

Predicting The Energy Output Of Wind Turbine Based On Weather Condition DEMO LINK : https://youtu.be/ICfu49Ud2HU

Different modeling techniques like multiple linear regression and random forest, etc. will be used for predicting the cement compressive strength. A comparative analysis will be performed to identify the best model for our prediction in terms of accuracy.

using sklearn

The purpose of this project was to analyze and predict housing prices using attributes or features such as square footage, number of bedrooms, number of floors, and so on.

Predicting sales volume at various stores

A simple example of random state in train test split using python

📗 This repository provides an in-depth exploration of the predictive linear regression model tailored for Jamboree Institute students' data, with the goal of assisting their admission to international colleges. The analysis encompasses the application of Ridge, Lasso, and ElasticNet regressions to enhance predictive accuracy and robustness.

Python ML Scripts