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car-price-prediction-with-machine-learning

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This repository contains the code and resources for a machine learning project aimed at predicting car prices based on various features. The project utilizes both Linear Regression and Random Forest Regression models to achieve accurate predictions.

  • Updated Jul 23, 2024
  • Jupyter Notebook

This project showcases Power BI skills by analyzing customer behavior and preferences in the automotive market. Using interactive dashboards, it provides insights into demographics, car brands, models, and purchasing trends, highlighting the use of Power BI for data-driven decisions.

  • Updated Aug 28, 2024

This repository presents a data-driven exploration into predicting car prices using a machine learning model based on linear regression, aimed at aiding a Chinese automobile company's entry into the competitive US market.

  • Updated Aug 2, 2023
  • Jupyter Notebook

Welcome to the "Car Price Prediction with Random Forest Regressor" repository! This project focuses on predicting the prices of cars using the power of machine learning and the Random Forest Regressor algorithm. If you're interested in the automotive industry, machine learning, or predictive modeling, this repository is a perfect starting point.

  • Updated Sep 29, 2023
  • Jupyter Notebook

"Developed a machine learning model to predict stock prices based on historical data and key market indicators. Implemented time series analysis, regression models, and deep learning algorithms to identify trends and forecast future prices. Utilized Python libraries like pandas, scikit-learn, and TensorFlow for data preprocessing, model training

  • Updated Aug 19, 2024
  • Jupyter Notebook

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