Last updated 11/2020MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHzLanguage: English | Size: 1.51 GB | Duration: 5h 11m
Bner and Advanced Customer Analytics in Python: PCA, K-means Clustering, Elasticity Modeling & Deep Neural Networks
What you'll learn
Master bner 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: sntation, targeting, positioning, marketing mix, and price elasticity;
Apply sntation on your customers, starting from raw data and reaching final customer snts;
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 sntation;
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.