Multiple Linear Regression with scikit-learn
By the end of this project, you will be able to:
- Build univariate and multivariate linear regression models using scikit-learn
- Perform Exploratory Data Analysis (EDA) and data visualization with seaborn
- Evaluate model fit and accuracy using numerical measures such as R² and RMSE
- Model interaction effects in regression using basic feature engineering techniques
This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your internet browser so you can just focus on learning. For this project, this means instant access to a cloud desktop with Jupyter Notebooks and Python 3.7 with all the necessary libraries pre-installed.
- You will be able to access the cloud desktop 5 times. However, you will be able to access instructions videos as many times as you want.
- This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
- Fecha Incio:14/06/2021
- Idioma: Inglés
- Universidad: Coursera Project Network
- Profesores: Snehan Kekre
- Certificado: Si