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GitHub / MNitin-Reddy / A-B-Testing-and-Regression-Analysis-for-Ad-Performance-Optimization

Analyzed the performance of Facebook and AdWords ads using A/B testing and regression analysis to identify trends, correlations, and cost-effectiveness. Key insights included distribution of clicks and conversions, monthly trends, and cost-per-conversion analysis to optimize ROI.

JSON API: http://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MNitin-Reddy%2FA-B-Testing-and-Regression-Analysis-for-Ad-Performance-Optimization

Stars: 0
Forks: 0
Open issues: 0

License: None
Language: Jupyter Notebook
Size: 1.33 MB
Dependencies parsed at: 7

Created at: 6 months ago
Updated at: 6 months ago
Pushed at: 6 months ago
Last synced at: 2 months ago

Topics: abtesting, data-science, hypothesis-testing, machine-learning, matplotlib, numpy, pandas, scikit-learn, scipy, seaborn, statsmodels

requirements.txt pypi