Implementation of Linear regression on Boston House Pricing and Diabetes data sets using python.

This code demonstrates how to integrate PySpark with datasets and perform simple data transformations. It loads a sample dataset using PySpark's built-in functionalities or reads data from external sources and converts it into a PySpark DataFrame for distributed processing and manipulation.

This project aims to solve the Vehicle Routing Problem (VRP) by addressing missing data using linear regression and predicting the time required for particular orders. Additionally, it predicts the optimal set of routes for a fleet of vehicles to traverse to deliver to a given set of customers efficiently.

This project involves parsing bike-sharing data from the CityBikes API and merging it with location-based details from Foursquare and Yelp APIs, conducting data exploration, visualization, and regression modeling to examine the correlation between bike station characteristics and adjacent points of interest.

A Fun Project - Using LinearRegression, Predicting the Value.

This linearRegression.py file contains the codes to create a linear regression model based on some data which contain information about a student's study duration(in hrs per day) in relation with the marks stored by the student. At the end the model also predicts for a student whose study duration is 9.25 hr/day.

A script to find the stock value of a company using semantic analysis and Machine Learning Algorithms

In Supervised Machine Learning, Regression algorithms helps us to build a model by which we can predict the values of a dependent variable from the values of one or more independent variables. For example, predicting future demand for a product based on previous demand. In this tutorial, we will use linear regression to predict salaries using Li…

Machine learning Algorithms but the implementations done by me and no external libraries used

This repository contains code for Machine Learning (beginner level) using Python.

This GitHub repository contains code for a student performance prediction model utilizing linear regression. The model is built using relevant student data features and implements one-hot encoding for categorical variables. The repository includes data preprocessing, model training, evaluation, and prediction visualization using matplotlib.

Creates and uses a ml tabular regression model to predict housing prices based on economical and environmental factors

A simple Linear Regression project from scratch in Python 3.

Estimating CPI stacks of 6 benchmark programs using Linear regression with regularization.

Machine learning model is used to get the accurate prediction for house's price using linear regression model using house size, age and rooms size as feature vector.

This project is a Python-based web scraping script designed to collect and analyze car listing data from Cars.com. The script focuses on extracting information for Porsche 911 models within a specified location (e.g., Quincy, MA). It cleans and transforms the data, visualizes key trends, and determines price depreciation over time.

KI-Tool zur Schätzung von Wohnungspreisen in Leipzig basierend auf 9 Merkmalen, trainiert auf historischen ImmoScout24-Daten. (Configs&Daten nicht öffentlich)

Build a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python. Predict delivery time using sorting time

Build a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python. Build a prediction model for Salary_hike

This project predicts Apple stock prices using linear regression. It's based on historical stock price data and uses Python and popular data science libraries like Pandas, NumPy, Matplotlib, and scikit-learn.