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lgbmregressor

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This repo has been developed for the Istanbul Data Science Bootcamp, organized in cooperation with İBB and Kodluyoruz. Prediction for house prices was developed using the Kaggle House Prices - Advanced Regression Techniques competition dataset.

  • Updated Jul 10, 2022
  • Jupyter Notebook

l train and evaluate multiple time-series forecasting models using the Store Item Demand Forecasting Challenge dataset from Kaggle. This dataset has 10 different stores and each store has 50 items, i.e. total of 500 daily level time series data for five years (2013–2017).

  • Updated Jun 13, 2024
  • Jupyter Notebook

Kaggle Competition : Predicting house prices using a collection of advanced regression techniques and data visualization with plotly

  • Updated Jan 11, 2021
  • Jupyter Notebook

Rusty Bargain is a used car buying and selling company that is developing an app to attract new buyers. My job as data science is to create a model that can determine the market value of a car.

  • Updated Jul 3, 2024
  • Jupyter Notebook

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