Customer Analytics in Python
Beginner and Advanced Customer Analytics in Python: PCA, K-means Clustering, Elasticity Modeling & Deep Neural Networks
4.44 (1589 reviews)
16 357
students
5 hours
content
Sep 2024
last update
$99.99
regular price
What you will learn
Master beginner and advanced customer analytics
Learn the most important type of analysis applied by mid and large companies
Gain access to a professional team of trainers with exceptional quant skills
Wow interviewers by acquiring a highly desired skill
Understand the fundamental marketing modeling theory: segmentation, targeting, positioning, marketing mix, and price elasticity;
Apply segmentation on your customers, starting from raw data and reaching final customer segments;
Perform K-means clustering with a customer analytics focus;
Apply Principal Components Analysis (PCA) on your data to preprocess your features;
Combine PCA and K-means for even more professional customer segmentation;
Deploy your models on a different dataset;
Learn how to model purchase incidence through probability of purchase elasticity;
Model brand choice by exploring own-price and cross-price elasticity;
Complete the purchasing cycle by predicting purchase quantity elasticity
Carry out a black box deep learning model with TensorFlow 2.0 to predict purchasing behavior with unparalleled accuracy
Be able to optimize your neural networks to enhance results
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2643050
udemy ID
06/11/2019
course created date
20/11/2019
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