Causal Inference

Double Machine Learning Approach you own this product

This project is part of the liveProject series Causal Inference and Personalization
prerequisites
basics of Python • basics of data science and machine learning
skills learned
pandas to manipulate tabular data • linear regression for causal inference • use machine learning to make causal models for personalization
Matheus Facure
1 week · 6-8 hours per week · INTERMEDIATE
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liveProject This project is part of the liveProject series Causal Inference and Personalization liveProjects give you the opportunity to learn new skills by completing real-world challenges in your local development environment. Solve practical problems, write working code, and analyze real data—with liveProject, you learn by doing. These self-paced projects also come with full liveBook access to select books for 90 days plus permanent access to other select Manning products. $19.99 $29.99 you save $10 (33%)
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Look inside

In this liveProject, you’ll utilize machine learning for treatment effect estimation in order to help an e-commerce company deliver targeted discounting to the most profitable customers. You’ll build a model that predicts the effect of a discount on a customer following a causal model, maximizing profits for the business.

This project is designed for learning purposes and is not a complete, production-ready application or solution.

book resources

When you start your liveProject, you get full access to the following books for 90 days.

project author

Matheus Facure
Matheus Facure is an economist, data scientist and causal inference specialist at Nubank. He currently works with adding causal inference capabilities to machine learning models with application in the credit card business, and acts as a consultant for other business areas inside Nubank, such as personal loans and marketing.

prerequisites

This liveProject is for data scientists with knowledge of Python, machine learning, and statistics. To begin this liveProject you will need to be familiar with the following:


TOOLS
  • Basics of Python
  • Basics of pandas
  • Basics of Matplotlib
  • Basics of NumPy
TECHNIQUES
  • Basics of data science and machine learning
  • Basics of causal inference

you will learn

In this liveProject, you’ll learn core skills of causal inference and how to apply them to practical business scenarios.


  • pandas to manipulate tabular data
  • Linear regression for causal inference
  • Use machine learning to make causal models for personalization
  • Use a causal model to make a recommendation on which type of customers we should give discounts to

features

Self-paced
You choose the schedule and decide how much time to invest as you build your project.
Project roadmap
Each project is divided into several achievable steps.
Get Help
While within the liveProject platform, get help from other participants and our expert mentors.
Compare with others
For each step, compare your deliverable to the solutions by the author and other participants.
book resources
Get full access to select books for 90 days. Permanent access to excerpts from Manning products are also included, as well as references to other resources.
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