Skip to content
Analytics and data science business case studies to identify opportunities and inform decisions about products and features. Topics include Markov chains, A/B testing, customer segmentation, and machine learning models (logistic regression, support vector machines, and quadratic discriminant analysis).
Branch: master
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
.ipynb_checkpoints update Mar 6, 2019
Datasets update Mar 6, 2019
Market Basket Analysis final project submission Dec 12, 2017
User Preferences and HB Modeling
markov chains
mysql_database_files
.DS_Store update Mar 6, 2019
.gitignore
Churn Analysis_Customer Lifetime Value.key uploaded markov chains pdf slides Dec 18, 2017
Churn Analysis_Customer Lifetime Value.pdf
DSCI6006-4.1-Lecture AB Testing .ipynb AB testing Mar 20, 2017
Datasets.zip added datasets Jun 26, 2017
Decision Rules.ipynb
Decision Rules.key customer segmentation Mar 20, 2017
Design of AB Testing.ipynb update Mar 6, 2019
HB Part-Worth Estimation results.txt final project submission Dec 12, 2017
HB_notes.txt final project submission Dec 12, 2017
Hierarchical Bayes Model.pptx added presentation slides Dec 12, 2017
Hospital Readmissions - binary classification.ipynb update Oct 12, 2018
Hospital Readmissions Analysis - slides.pdf slides and notebook Apr 5, 2017
Hospital Readmissions Analysis.key tahoe readmissions slides Mar 20, 2017
Logistic Regression.ipynb update Mar 20, 2017
Marketing Email Campaign.ipynb
Modeling Customer Relationships as Markov Chains.ipynb
README.md Update README.md Mar 20, 2017
jacobs-marketing analytics.ipynb update Jul 4, 2017
markov chains.zip markov chains zip Jan 16, 2018
price optimization of financial services.ipynb update Oct 12, 2018
purchases.ipynb
purchases.txt markov chains update Dec 14, 2017

README.md

Analytics-Case-Studies

Analytics and data science business case studies to identify opportunities and inform decisions about products and features.

Topics include Markov chains, A/B testing, customer segmentation, and machine learning models (logistic regression, support vector machines, and quadratic discriminant analysis).

You can’t perform that action at this time.