Data Science in Python: Regression & Forecasting
Data Science in Python: Regression & Forecasting
Learn Python for Data Science & Machine Learning, and build regression and forecasting models with hands-on projects
Created by Maven Analytics, Chris Bruehl | 8.5 hours on-demand video course
This is a hands-on, project-based Data Science in Python: Regression & Forecasting course designed to help you master the foundations for regression analysis in Python. We’ll start by reviewing the data science workflow, discussing the primary goals & types of regression analysis, and do a deep dive into the regression modeling steps we’ll be using throughout the course.
You’ll learn to perform exploratory data analysis, fit simple & multiple linear regression models, and build an intuition for interpreting models and evaluating their performance using tools like hypothesis tests, residual plots, and error metrics. We’ll also review the assumptions of linear regression, and learn how to diagnose and fix each one.
What you’ll 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
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Who this course is for:
- 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
