Predict Employee Turnover with scikit-learn
Welcome to this project-based course on Predicting Employee Turnover with Decision Trees and Random Forests using scikit-learn. In this project, you will use Python and scikit-learn to grow decision trees and random forests, and apply them to an important business problem. Additionally, you will learn to interpret decision trees and random forest models using feature importance plots. Leverage Jupyter widgets to build interactive controls, you can change the parameters of the models on the fly with graphical controls, and see the results in real time! 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, you’ll get instant access to a cloud desktop with Python, Jupyter, and scikit-learn pre-installed.
由 SJ 提供2020年4月27日
Excellent course for those who knowledge on the topics mentioned in the content.
由 AO 提供2020年10月29日
It really worth the time and I was exposed to new approach to codes and algorithm.
由 RD 提供2020年9月28日
Great course. It goes to the point about decision trees and random forests.
由 LY 提供2020年5月4日
I was looking for Elaborated explanation of the project and implement it to clear the concept.
This course did explain it all.