Design of Experiments and Analysis
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Updated
Oct 5, 2020 - Python
Design of Experiments and Analysis
Scientific Research Reasoning Engine for analyzing experimental evidence, evaluating scientific claims, and generating structured research reports.
African language Speech Recognition - Speech-to-Text
A hands-on tutorial for understanding experimentation systems by building one
Statistical validity engine that audits A/B experiments across 8 checks:SRM, power, peeking, SUTVA, and more.
Statistical A/B testing analysis of marketing campaigns using hypothesis testing to compare performance based on key business metrics.
PyTorch simulator for Federated Reconstruction (FedRecon) on MovieLens 1M.
A/B testing analysis of mobile-game retention using frequentist, bootstrap, Bayesian, and product-decision methods.
합성 제품 이벤트를 데이터 품질·A/B 테스트·3개 가드레일 검증과 의사결정 메모로 연결한 분석 워크플로
Randomised campaign analysis and doubly robust targeting evaluation using Python, SQL and scikit-learn.
African language Speech Recognition - Speech-to-Text
Marketing A/B testing case study with conversion uplift, hypothesis testing, confidence intervals, effect-size interpretation and power planning.
Ant colony simulation with pygame visualization, configurable experiments, and result analysis.
Product analytics decision engine for evaluating SaaS onboarding experiments using BigQuery, A/B testing, Power BI, and Streamlit.
This repo has a complete demonstration of performing experiment tracking with mlflow
Ecommerce growth analytics platform with funnel intelligence, conversion drop-off analysis, retention analytics, experimentation dashboards, and executive KPI monitoring.
Audit completed A/B experiment readouts for SRM, peeking risk, practical significance, guardrail movement, and pre-period imbalance. Zero dependencies. Structured PASS/WARN/FAIL reports in JSON, Markdown, and HTML.
Release intelligence for AI agents that turns behavior, product metrics, statistical investigation, economics, and human feedback into evidence-backed SHIP/HOLD/ROLLBACK decisions.
Корпус синтетических A/B-кейсов: в каждом ровно одна заложенная ошибка. Материал для проверки AI-аналитика.
FastAPI web app that analyzes A/B test CSVs and generates AI-driven experiment insights with automatic stats, uplift, and p-values.
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