model stability

GuanYuan Data Tech Team

Sep 8, 2022 · Artificial Intelligence

How AI Reinforcement Learning Transforms Smart Replenishment in Retail

This article examines the technical challenges of intelligent replenishment—model stability, complexity, generalization, and interpretability—and explains how a few‑shot imitation learning and inverse reinforcement learning framework can overcome these issues to deliver reliable, low‑cost AI‑driven supply‑chain decisions.

AIimitation learningmodel stability

0 likes · 22 min read

How AI Reinforcement Learning Transforms Smart Replenishment in Retail

JD Tech Talk

Jun 4, 2020 · Artificial Intelligence

The Art and Science of Feature Engineering: Importance, Methods, and Automation

Feature engineering, which occupies the majority of data scientists' time, is essential for building high‑performing machine‑learning models and involves careful data quality control, diverse construction techniques, rigorous selection, and emerging automation efforts, all of which demand domain expertise and systematic practice.

AIAutomationFeature Engineering

0 likes · 14 min read

The Art and Science of Feature Engineering: Importance, Methods, and Automation

JD Tech Talk

May 29, 2020 · Artificial Intelligence

The Black Art of Feature Engineering: Importance, Techniques, and Automation

This article explains why feature engineering consumes most of a data scientist's time, outlines its critical steps—including data observation, cleaning, transformation, selection, and reduction—covers practical issues such as missing‑value handling, data leakage, and feature stability, and discusses both manual and automated approaches for building effective machine‑learning models.

AutomationFeature Engineeringdata preprocessing

0 likes · 14 min read

The Black Art of Feature Engineering: Importance, Techniques, and Automation