Machine Learning dashboard that predicts student performance using Linear Regression (implemented from scratch) with Streamlit visualization.

Predicting the price of Bitcoin closes with machine learning method and testing linear modes and using linear regression model.

predict house prices in America, in the first part, we clean the dataset and then, because our data is continuous, we use linear regression, we train our dataset with linear regression, and then we test it. Of course, we should know that the data of the house can never be accurately predicted

Apache Spark Machine Learning project using MLlib and Linear Regression on Databricks!

Use plain Python to implement classic(basic) machine learning methods from scratch | CSCE633

Laptop Price Prediction using Machine Learning. This project analyzes laptop specifications like RAM, CPU, storage, and GPU to predict prices using data preprocessing, EDA, and a Linear Regression model.

Deployed a House Price Predicting App end-to-end with Streamlit. Built a Simple Linear Regression from scratch with Numpy, Pandas, Matplotlib and Salary Dataset and from kaggle.

The goal of this problem is to predict the Price of an Old car based on the variables provided in the data set.

It will predict the SGPA of a student on the basis of marks obtain in Internal Theory and Lab, External Theory and Lab along with the total number of backs and UFM cases.

In this project, we tried to predict the prices of other houses according to the values ​​of these features with the model we obtained by training a data set containing some features and prices of real houses with linear regression and decision tree regression methods

A sophisticated geospatial analysis framework utilizing 36-dimensional urban feature engineering and comparative model benchmarking (Lasso, Ridge, Random Forest). Features innovative population density proxy estimation and interactive visualization to optimize retail expansion strategies with a 97.7% predictive accuracy.

A Prediction Model is a statistical or machine learning model used to predict an outcome based on input data. These models are widely used in fields like finance, marketing, and healthcare to forecast trends or behaviors.

Machine Learning Models trained on dataset with over 300+ authentic real customer reviews

A machine learning project that predicts the number of Olympic medals a country's team will win, using Linear Regression trained on historical Olympic data.

This repository contains R projects focused on statistical analysis, using techniques like EDA, Hypothesis Testing, ANOVA, Normalization, and Linear Regression. Each project includes datasets, R scripts, results (plots, tables), and a detailed README for insights and methodology.

End-to-end machine learning project predicting house prices using Python, Pandas, NumPy, Matplotlib, Scikit-learn, and regression models with data preprocessing and evaluation.

This web application predicts the number of goals scored by a team in the Champions League based on various statistical parameters. It uses a linear regression model trained on a historical dataset of team performances.

Car price prediction using Linear Regression with real-world Pakistani car data.

E-Commerce Customer Analysis & Predictive Modeling project 🚀

Predict customer lifetime value of e-commerce customers using ML algorithms