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NetEase Yanxuan Technology Product Team
NetEase Yanxuan Technology Product Team
Aug 29, 2022 · Artificial Intelligence

Building Yanxuan Machine Learning Platform: Architecture and Implementation

Yanxuan built a Kubeflow‑based machine‑learning platform that unifies data preprocessing, feature engineering, model training, validation, and deployment, using Smart‑jobs, Smart‑Infer, Smart‑backend, Airflow pipelines, Jupyter notebooks, and Istio‑enhanced inference services to boost algorithm engineers’ efficiency and integrate with Kubernetes, HDFS, and Hive.

Airflow orchestrationAlgorithm DevelopmentInference Service
0 likes · 14 min read
Building Yanxuan Machine Learning Platform: Architecture and Implementation
ITPUB
ITPUB
May 27, 2022 · Databases

How HugeGraph’s Self‑Built Graph Computing Tackles Large‑Scale Graph Challenges

This article explains the fundamentals of graph computing, compares it with traditional processing, outlines industry challenges such as partitioning and load imbalance, and details HugeGraph’s self‑developed architecture, key technical solutions, and how developers can create and deploy graph algorithms.

Algorithm DevelopmentData PartitioningGraph Database
0 likes · 14 min read
How HugeGraph’s Self‑Built Graph Computing Tackles Large‑Scale Graph Challenges
Alibaba Cloud Developer
Alibaba Cloud Developer
Jun 8, 2021 · Artificial Intelligence

Can Low‑Code Bridge the Gap Between Business and AI? Insights on Its Future

The article explores how low‑code platforms can complement traditional algorithm development, enhance collaboration between business users and engineers, and accelerate big‑data and AI initiatives by improving data cleaning, modular design, and feedback loops, while highlighting the trade‑offs of abstraction and flexibility.

AIAlgorithm DevelopmentBig Data
0 likes · 9 min read
Can Low‑Code Bridge the Gap Between Business and AI? Insights on Its Future
MaGe Linux Operations
MaGe Linux Operations
Jul 30, 2017 · Artificial Intelligence

Why Python Dominates Data Mining: Clear Syntax, Rich Libraries, and Speed Trade‑offs

Python is favored for data‑mining algorithms because its clear syntax, built‑in advanced data structures, easy text handling, extensive libraries, and widespread community support outweigh its slower execution speed compared to Java or C, allowing rapid development and seamless integration with high‑performance code when needed.

Algorithm DevelopmentPythondata mining
0 likes · 5 min read
Why Python Dominates Data Mining: Clear Syntax, Rich Libraries, and Speed Trade‑offs
JD Retail Technology
JD Retail Technology
May 10, 2017 · Artificial Intelligence

JD Data Algorithm Competition: Solving Shopping Dilemmas with AI

The JD Data Algorithm Competition aims to help shoppers overcome decision paralysis by using advanced algorithms to match users with products they'll love, featuring diverse participants from students to professionals competing for prizes and potential real-world implementation.

Algorithm DevelopmentArtificial IntelligenceContest
0 likes · 3 min read
JD Data Algorithm Competition: Solving Shopping Dilemmas with AI