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

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

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

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

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

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

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

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.

This project focuses on forecasting cryptocurrency prices to aid in investment decisions, risk management, and market understanding. It aims to enhance predictive models for digital asset markets, providing more reliable insights for investors and traders.

Stock price prediction for 5 years from now

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.

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.