online experimentation

DataFunSummit

Dec 26, 2023 · Artificial Intelligence

Applying Causal Inference Tools for Growth Scenarios in Industry

This article explains why causal inference tools are essential for industrial growth, outlines data‑flow standards such as randomized controlled trials, discusses model selection including causal forests and policy learning, and describes evaluation, offline simulation, and resource‑constrained optimization for deploying causal models in production.

AIcausal forestcausal inference

0 likes · 12 min read

Applying Causal Inference Tools for Growth Scenarios in Industry

DataFunSummit

Jul 14, 2023 · Artificial Intelligence

Iterative Evolution of JD Search EE System: Adaptive Exploration, Scenario Modeling, Scoring‑Insertion Consistency, and Context‑Aware Brand Store Detection

This article details the multi‑stage evolution of JD's search Explore‑Exploit (EE) system—covering an adaptive dynamic detection model, scenario‑modeling upgrades, end‑to‑end scoring and insertion consistency, and context‑aware brand/store dimension detection—demonstrating how each iteration improves result diversity, user experience, and key online metrics while maintaining search efficiency.

E-commerceadaptive modelingexplore‑exploit

0 likes · 24 min read

DataFunSummit

Jan 30, 2023 · Fundamentals

Understanding AB Testing: Design, Execution, and Analysis

This article explains the purpose, methodology, and practical examples of AB testing, describing how randomized traffic segmentation, logging, and metric analysis enable data‑driven product decisions across various industries while also noting its widespread adoption and promotional resources.

AB testingdata-drivenexperiment design

0 likes · 7 min read

Understanding AB Testing: Design, Execution, and Analysis