Mining Quality Prediction Using Machine & Deep Learning
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 regressio
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- Level Beginner
- Duration 2 hours
- Course by Coursera Project Network
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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.Modules
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- Graded Quiz: Test your Project Understanding
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- Mining Quality Prediction Using Machine and Deep Learning
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- Project-based Course Overview
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Discover the essentials of mining quality prediction using machine and deep learning in this beginner-friendly, 1.5-hour course by Coursera. Led by expert instructors, you'll delve into linear regression theory, data visualization, exploratory data analysis, and model training using Python libraries. Perfect for IT and computer science enthusiasts, this free course covers key performance indicators and model evaluation techniques.
Ryan Ahmed