Using simulated data, public datasets, and Jupyter notebooks, this course will take you through: Simple linear regressions and multiple linear regression concepts, the mathematics behind linear regression models, how to manually implement a linear regression model, how to use
scikit-learn Python packages to implement a linear regression model, how to validate a model and measure it's efficacy, and how to handle common issues. Then, you will be given the opportunity to build a linear regression model from start to finish in a self-guided project.
- Python (including
- Basic maths and statistics (introductory calculus helpful but not necessary)