You will learn more about Decision Trees, how to build one and challenges faced

• In Class Instruction: 2 Hours

  • In Class code along Dataset: Lending Club Dataset

• Skills Rehearsed

  • Apply Decision Tree algorithm in Python using sklearn

• Recap of previous session
• Instructor Concept building
• Periodic Recap - Closer to the end of session
• In Class Assignments - Motivation

1. https://medium.com/data-science-group-iitr/decision-trees-decoded-c70b4f7ff542

1. Understand why to use a Decision Tree
2. Learn how to make a Decision Tree
3. Learn about the challenges with Decision Tree
4. Learn how to deal with Over-fitting

Check the Jupyter Notebook in the top right of the screen

1. http://www.saedsayad.com/decision_tree_overfitting.htm
2. https://stackoverflow.com/questions/1859554/what-is-entropy-and-information-gain
3. http://www.alanfielding.co.uk/multivar/crt/dt_example_04.htm

Lending Club is a peer-to-peer lending company, headquartered in San Francisco. Through personal, auto refinancing loans and medical financing. Lending Club offers the borrowing and investing solution right for you. Build a machine learning model that can reliably predict if a loan will be paid off or not and does a good job of filtering out high percentage of loan defaulters.