Mining Quality Prediction Using Machine & Deep Learning
About this course
In this 1.5-hour long project-based course, you will be able to: - Understand the theory and intuition behind Simple and Multiple Linear Regression. - Import Key python libraries, datasets and perform data visualization - Perform exploratory data analysis and standardize the training and testing data. - Train and Evaluate different regression models using Sci-kit Learn library. - Build and train an Artificial Neural Network to perform regression. - Understand the difference between various regression models KPIs such as MSE, RMSE, MAE, R2, and adjusted R2. - Assess the performance of regression models and visualize the performance of the best model using various KPIs.
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- 8/35
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What you'll learn
- understand the principles of linear regression
- import and visualize data using Python
- perform exploratory data analysis
- train and evaluate regression models
- build an artificial neural network for regression
- interpret regression performance metrics such as MSE and R2
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