machine learning platform

iQIYI Technical Product Team

Jun 28, 2024 · Artificial Intelligence

Feature Center Overview in iQIYI's Opal Machine Learning Platform

The Feature Center in iQIYI’s Opal platform centralizes feature creation, storage, and real‑time access through a drag‑and‑drop DAG workflow and DSL‑driven transformations, handling massive QPS and low‑latency demands while enabling fast business iteration, cross‑team reuse, and monitoring for advertising, recommendation, and risk‑control applications.

Big DataFeature EngineeringOpal

0 likes · 13 min read

Feature Center Overview in iQIYI's Opal Machine Learning Platform

DataFunTalk

Oct 20, 2023 · Artificial Intelligence

Building the ATLAS Automated Machine Learning Platform at Du Xiaoman: Architecture, Practices, and Optimizations

This article describes how Du Xiaoman tackled the high cost, instability, and long cycles of AI algorithm deployment by building the ATLAS automated machine learning platform, detailing its four‑stage workflow, component platforms, scaling and efficiency techniques, and practical Q&A for practitioners.

AI deploymentAutoMLData Parallelism

0 likes · 22 min read

Building the ATLAS Automated Machine Learning Platform at Du Xiaoman: Architecture, Practices, and Optimizations

Tencent Advertising Technology

Mar 30, 2023 · Artificial Intelligence

Tencent's Taiji Machine Learning Platform: End-to-End MLOps for Advertising

Tencent’s Taiji machine learning platform, a cloud‑native, distributed parameter‑server system, provides end‑to‑end MLOps for advertising by integrating data ingestion, feature engineering, model training, evaluation, deployment, and monitoring, supporting massive models up to billions of parameters while improving efficiency, scalability, and resource management.

Feature EngineeringModel Deploymentadvertising

0 likes · 18 min read

Tencent's Taiji Machine Learning Platform: End-to-End MLOps for Advertising

DataFunTalk

Feb 18, 2023 · Artificial Intelligence

Building the ATLAS Automated Machine Learning Platform at Du Xiaoman: Architecture, Optimization, and Practical Insights

This article details Du Xiaoman's development of the ATLAS automated machine learning platform, covering business scenarios, AI algorithm deployment challenges, the end‑to‑end production workflow, platform components such as annotation, data, training and deployment, as well as optimization techniques like AutoML, meta‑learning, NAS, and large‑scale parallelism, concluding with lessons learned and future directions.

AI deploymentAutoMLData Engineering

0 likes · 20 min read

Building the ATLAS Automated Machine Learning Platform at Du Xiaoman: Architecture, Optimization, and Practical Insights

Tencent Advertising Technology

Feb 17, 2023 · Big Data

Cost Optimization and Mixed‑Resource Deployment in Tencent's Taiji Machine Learning Platform

The article details how Tencent's Taiji machine‑learning platform reduces training costs and improves efficiency for large‑scale advertising models by leveraging cloud‑native mixed‑resource strategies—including online idle, offline elastic, and compute‑resource sharing—while maintaining high service stability through advanced scheduling, fault‑tolerance, and resource‑prediction techniques.

Big DataCost OptimizationResource Scheduling

0 likes · 16 min read

Cost Optimization and Mixed‑Resource Deployment in Tencent's Taiji Machine Learning Platform

DataFunTalk

Feb 14, 2023 · Artificial Intelligence

Cost Optimization and Mixed‑Resource Deployment in Tencent Taiji Machine Learning Platform for Large‑Scale AI Models

The article describes how Tencent's Taiji machine learning platform leverages cloud‑native mixed‑resource strategies—including online idle, tidal, and compute resources—to reduce training costs, improve stability, and support large‑scale AI model training for advertising and other services.

AICost OptimizationLarge Models

0 likes · 17 min read

Cost Optimization and Mixed‑Resource Deployment in Tencent Taiji Machine Learning Platform for Large‑Scale AI Models

Dada Group Technology

Nov 18, 2022 · Artificial Intelligence

JD Daojia Machine Learning Platform: Architecture and Implementation

This article introduces JD Daojia's machine learning platform, detailing its architecture, implementation principles, and practical applications in various business scenarios, achieving significant improvements in recommendation and search systems.

Feature EngineeringGraph Neural NetworksKubernetes

0 likes · 28 min read

JD Daojia Machine Learning Platform: Architecture and Implementation

Xiaohongshu Tech REDtech

Nov 11, 2022 · Artificial Intelligence

Large-Scale Deep Learning Systems and Their Application at Xiaohongshu (RED)

Xiaohongshu’s in‑house LarC platform powers real‑time, multimodal recommendation, life‑search, and generative‑AI commercial content for its 200 million‑user community by processing billions of daily feedback samples, employing conflict‑free parameter servers, diversified sequence modeling, and large‑scale representation learning to deliver personalized, fresh, and diverse user experiences.

AI infrastructureXiaohongshularge-scale deep learning

0 likes · 13 min read

Large-Scale Deep Learning Systems and Their Application at Xiaohongshu (RED)

vivo Internet Technology

Oct 9, 2022 · Artificial Intelligence

vivo Machine Learning Platform: Architecture Design and Practice

vivo’s machine‑learning platform, built for its massive app‑store and e‑commerce ecosystem, streamlines data processing, model training, and deployment through quota‑based resource management, a custom ultra‑large‑scale TensorFlow‑vlps framework, OpenAPI‑driven training, and Jupyter‑integrated interactive development, boosting efficiency for billions of samples and features.

Feature EngineeringModel DeploymentResource Scheduling

0 likes · 12 min read

vivo Machine Learning Platform: Architecture Design and Practice

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 DevelopmentFeature Engineering

0 likes · 14 min read

Building Yanxuan Machine Learning Platform: Architecture and Implementation

DataFunSummit

Feb 4, 2021 · Artificial Intelligence

Full-Stack Machine Learning Platform: Architecture, Key Factors, and Implementation Details

This article examines the evolution of user data, computing power, and models, and presents the design principles, key architectural factors, and practical implementation techniques for building a full‑stack machine learning platform that supports large‑scale data processing, distributed training, and low‑latency online serving.

Resource Schedulingbig data integrationdata pipelines

0 likes · 15 min read

Full-Stack Machine Learning Platform: Architecture, Key Factors, and Implementation Details

DataFunTalk

Jul 1, 2020 · Artificial Intelligence

Architecture and Implementation of Autohome's Machine Learning Platform

The article presents a comprehensive overview of Autohome's one‑stop machine learning platform, detailing its background, architecture, resource scheduling, data processing, model training (including distributed deep learning), deployment, real‑world applications such as purchase‑intent and recommendation models, and future development directions.

AutoMLKubernetesSpark

0 likes · 19 min read

Architecture and Implementation of Autohome's Machine Learning Platform

Tencent Cloud Developer

May 29, 2018 · Artificial Intelligence

Intelligent Titanium TI-ONE: Tencent Cloud's One-Stop Machine Learning IDE

Intelligent Titanium TI-ONE is a one‑stop ML IDE on Tencent Cloud offering integrated data preparation, drag‑and‑drop algorithm development, automatic hyperparameter tuning, multi‑level collaboration, one‑click model deployment, and support for major frameworks such as TensorFlow, PyTorch, Angel and XGBoost, plus commercial features via GaiaStack.

AI PlatformModel DeploymentTI-ONE

0 likes · 10 min read

Intelligent Titanium TI-ONE: Tencent Cloud's One-Stop Machine Learning IDE