Proyek pertama predictive analytics untuk membangun model machine learning yang dapat memprediksi harga sewa rumah dan apartement di India.

This repository contains a comprehensive analysis and predictive modeling project for the National Iranian Gas Company. The project aims to explore gas consumption data, identify patterns and anomalies, and predict future consumption trends using various statistical and machine learning models.

A collection of machine learning models for predicting laptop prices

This project uses machine learning to predict the price of a used car. The model is trained on a dataset of historical car sales data, and it can then be used to predict the price of a car based on its features.

Food Delivery Time Prediction using Machine Learning

Big Mart Sales Prediction is a data-driven project aiming to forecast product sales accurately across Big Mart outlets. Leveraging machine learning and comprehensive datasets, our project empowers retailers to optimize inventory, enhance profitability, and make informed decisions in the dynamic world of retail.

The objective of the project is to conduct a comprehensive analysis of a dataset of data science job postings, identifying the most important factors that influence salaries. Build predictive models that can be used to predict salaries for data science professionals, taking into account factors such as experience level, education, skills etc.

Developed student performance predicting model, showing strong understanding of predictive modeling techniques.

Predicting cement strength

This mini-project involves experimenting with a variety of classification and regression models, exploring different techniques to understand their behaviors and applications in predictive analytics.

Predict laptop prices using machine learning. This project leverages multiple linear regression to achieve an 82% prediction precision. Explore the influence of features like brand, specs, and more on laptop prices.

Predicting Compressive Strength of Concrete

This repository contains a machine learning model aimed at predicting student performance across various metrics. Utilizing a diverse set of Machine Learning Regression algorithms, the model predicts scores based on demographic and academic variables.This project demonstrates robust approach to leveraging machine learning for educational outcomes.

The purpose of this notebook is to develop an automated function to predict the price of a diamond based on its given features (cut, color, dimensions, etc.). We will create a machine learning model which can estimate these values. We need to find continuous data, so we will perform a regression task. We will use supervised learning to find the …