Hey future Business Scientists, welcome back to my Business Science channel. This is Learning Lab 90 where I shared how I do Causal Machine Learning and Causal Inference in Python. This FULL TUTORIAL is JAMMED to the brim with value. I cover an in-depth Python Marketing Analytics workshop that covers making Marketing Experiments, exploratory analysis with Correlation Funnels, modeling bookings and cancellations, working with statsmodels to make Logistic Regression Models, using Causal Machine Learning with Uber's CausalML, and more!
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Table of Contents
00:00 Causal Machine Learning in Python (Feat. CausalML)
01:24 Agenda
03:39 My background
07:21 Introduction to Causal Machine Learning (Quick Concepts)
12:42 Full Code Tutorial: Hotel Cancellations Business Case Study
13:00 Project Setup
17:03 Part 1: Analyzing Hotel Cancellations (Pre-Experiment)
20:05 Cost Analysis: How many people cancel?
22:18 Data Preprocessing
26:22 Cancellation Correlation Analysis (Correlation Funnel)
35:54 Causal Hypothesis: Will reducing lead times also reduce cancellations?
42:50 Problem: Need to consider confounders
46:48 Part 2: Marketing Experiment to Reduce Hotel Cancellations
50:00 Experiment Analysis: How many people accept the offer and does it reduce cancellations?
53:04 Causal Machine Learning Analysis
54:00 Uplift Tree (Decision Tree Classifier)
56:56 Interpretable Causal Machine Learning (SHAP)
1:02:00 Causal Optimize Module (Adding Treatment Costs $$$)
1:05:22 Uplift Calculations: Calculating Return on Investment (ROI)
1:07:47 How to make $150,000 with data science
#DataScience #Python #MachineLearning