machine-learning-regression

Built house price prediction model using linear regression and k nearest neigrs and used machine learning techniques like ridge, lasso, and gradient descent for optimization in Python

The objective of this project is to study the COVID-19 outbreak using basic statistical techniques and make short term predictions using ML regression methods.

This repo covers the basic machine learning regression projects/problems using various machine learning regression techniques and MLP Neural Network regressor through scikit learn library

Protein-protein interaction Binding Affinity Prediction

This project aims to build a predictive model that could predict the number of rental bikes required for each hour using the Seoul Bike Sharing dataset. Linear regression, Lasso (L1), Ridge (L2), ElasticNet, Decision Tree, Random Forest, and XGBoost algorithms are used to build a model to predict the number of rental bikes required for each hour.

Data analysis with Python to building and evaluating data models.

The task is to build a machine learning regression model will predict the number of absent hours. As Employee absenteeism is a major problem faced by every employer which eventually lead to the backlogs, piling of the work, delay in deploying the project and can have a major effect on company finances. The aim of this project is to find an issue…

🏡 Empower property market decisions with a machine learning model predicting house prices using the Boston Housing dataset. 💸🏠💹

In this repository, delve into the realm of regression modeling featuring an array of algorithms applied to diverse datasets. Explore the strengths and nuances of different regression techniques, providing a comprehensive overview for anyone interested in predictive modeling.

CODSOFT Data Science Internship Project Tasks.

Machine Learning Regression use case notebooks

Multi-Linear and Binary Logistic Regression in C.

The latex code of my bachelor thesis at Sapienza University of Rome

This is my college practice work, where i try to learn and cover all the tree based regression algorithms (preferably in python).

This is my college practice work, where i try to learn and cover all the regression algorithms (preferably in python)

Machine Learning Projects

Project uses machine learning algorithms to predict house prices based on features like location, size, and amenities. It involves data preprocessing, feature engineering, and training models to achieve accurate predictions. The project aims to provide insights for real estate investment and pricing strategies.

Agricultural Yield and Population Forecasting: Utilizing machine learning to enhance crop yield and predict global population trends, informing sustainable development and policy decisions.