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regression-analysis

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A Linear Regression model to predict the car prices for the U.S market to help a new entrant understand important pricing variables in the U.S automobile industry. A highly comprehensive analysis with detailed explanation of all steps; data cleaning, exploration, visualization, feature selection, model building, evaluation & MLR assumptions validity.
  • Updated Jul 28, 2020
  • Jupyter Notebook

It is from a kaggle competition where we have to predict the future sales using Machine Learning or Deep Learning. It is a Advanced Regression Problem where Statistics and time series analysis is also required. This problem can be very well done by Deep Learning's Model Recurrent Neural Networks.
  • Updated Apr 20, 2019
  • Jupyter Notebook

It is a Competition for Regression Challenge held by Kaggle, It is based on a Avito Dataset whose size is 123GB which can be accessed from Kaggle, I have done Data Pre-processing, feature engineering, feature extraction, data visualization, machine learning, stacking and boosting
  • Updated Apr 6, 2019
  • Jupyter Notebook

Understand the relationships between various features in relation with the sale price of a house using exploratory data analysis and statistical analysis. Applied ML algorithms such as Multiple Linear Regression, Ridge Regression and Lasso Regression in combination with cross validation. Performed parameter tuning, compared the test scores and suggested a best model to predict the final sale price of a house. Seaborn is used to plot graphs and scikit learn package is used for statistical analysis.
  • Updated Jan 19, 2018
  • Jupyter Notebook

Sensor data of a renowned power plant has given by a reliable source to forecast some feature. Initially the work has done with KNIME software. Now the goal is to do the prediction/forecasting with machine learning. The idea is to check the result of forecast with univariate and multivariate time series data. Regression method, Statistical method.
  • Updated Jul 9, 2020
  • Jupyter Notebook

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