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adaboost-regressor

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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.

  • Updated Jun 29, 2023
  • Jupyter Notebook

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.

  • Updated Aug 16, 2023
  • Jupyter Notebook

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.

  • Updated Aug 25, 2023
  • Jupyter Notebook

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.

  • Updated Sep 8, 2023
  • Jupyter Notebook
Diamond-Price-Modelling-Based-on-Their-Attributes

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 …

  • Updated Jun 29, 2022
  • Jupyter Notebook

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