Linear Regression, GLMs and GAMs with R

Learn Python for data science and machine learning, and build regression & forecast models w/ a top Python instructor!

Created by: Maven Analytics • 1,500,000 Learners
Empowering everyday people with life-changing data skills

Created by: Chris Bruehl
Lead Python Instructor at Maven Analytics

What Will I Learn?

• Master the machine learning foundations for regression analysis in Python
• Perform exploratory data analysis on model features, the target, and relationships between them
• Build and interpret simple and multiple linear regression models with Statsmodels and Scikit-Learn
• Evaluate model performance using tools like hypothesis tests, residual plots, and mean error metrics
• Diagnose and fix violations to the assumptions of linear regression models
• Tune and test your models with data splitting, validation and cross validation, and model scoring
• Leverage regularized regression algorithms to improve test model performance & accuracy
• Employ time series analysis techniques to identify trends & seasonality, perform decomposition, and forecast future values

Requirements

• We strongly recommend taking our Data Prep & EDA course first
• Jupyter Notebooks (free download, we'll walk through the install)
• Familiarity with base Python and Pandas is recommended, but not required

Target audience

• Data analysts or BI experts looking to transition into a data science role
• Python users who want to build the core skills for applying regression models in Python
• Anyone interested in learning one of the most popular open source programming languages in the world