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This is the curated pile of notebooks/small projects which contains linear and non-linear regression models.

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krashnagurme/linear-and-nonlinear-regression

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linear-and-nonlinear-regression

Linear Regression, Nonlinear Regression (RandomForestRegressor)

A.

  1. The .ipynb file contains the linear regression, OLS, and RandomForest Regressor model built on sales data. These models uses 5 independent variables to train themselves.
  2. Used data was quite good (Data Integrity). Due to which i didn't perform too many operations to get data cleaned/sorted for model feeding.
  3. Explored Techniques in notebook - Feature Encoding, Feature Selection, Standard Scaling, Pearson Correlation, Train and Test Split, Handling Outliers and Removing them.

B. Car-Price-Prediction

  1. predicting car price based on analysis of historical car data

C. USA housing price prediction