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Architects' Tech Alliance
Architects' Tech Alliance
Oct 17, 2017 · Artificial Intelligence

AI Learning Resources and Architecture Overview – A Curated Collection

This article presents a comprehensive collection of AI, machine learning, and deep learning learning materials, including historical overviews, technology architectures, application domains, and numerous downloadable resources such as tutorials, datasets, and code links, aimed at guiding enthusiasts and professionals in intelligent operations.

@DataDeep LearningResources
0 likes · 16 min read
AI Learning Resources and Architecture Overview – A Curated Collection
iQIYI Technical Product Team
iQIYI Technical Product Team
Oct 13, 2017 · Industry Insights

How iQIYI Built a Cloud‑Native Risk Control Platform to Stop Credential Stuffing

iQIYI’s security cloud team designed a data‑driven, cloud‑native risk control platform that unifies threat detection, rule management, and security knowledge across membership, video, e‑commerce and payment services, achieving sub‑5 ms latency, 24 billion daily requests, and near‑complete elimination of machine credential‑stuffing attacks.

cloud securitydata-driven securityiQIYI
0 likes · 17 min read
How iQIYI Built a Cloud‑Native Risk Control Platform to Stop Credential Stuffing
Meituan Technology Team
Meituan Technology Team
Oct 12, 2017 · Artificial Intelligence

Machine Learning Q&A: Data Imputation, Feature Selection, Recommendation Systems and More

The article answers ten machine‑learning questions, explaining how to impute missing behavior data, extract and select features, describe Meituan‑Dianping’s recommendation pipeline, suggest a beginner learning path, clarify L1 sparsity, recommend TextCNN for text, discuss search‑ranking sample bias, label generation for wide‑deep models, the shift to deep‑learning video detection, and the use of factorization machines for CTR with open‑source examples.

Deep LearningL1 RegularizationRecommendation Systems
0 likes · 7 min read
Machine Learning Q&A: Data Imputation, Feature Selection, Recommendation Systems and More
Hujiang Technology
Hujiang Technology
Oct 12, 2017 · Artificial Intelligence

An Overview of Machine Learning and Deep Learning: Definitions, Concepts, and Core Techniques

This article provides a comprehensive introduction to machine learning and deep learning, covering their definitions, classifications, key algorithms, neural network structures, core concepts such as generalization and regularization, and typical architectures like CNN and RNN, illustrated with numerous diagrams.

CNNNeural NetworksRNN
0 likes · 22 min read
An Overview of Machine Learning and Deep Learning: Definitions, Concepts, and Core Techniques
Huawei Cloud Developer Alliance
Huawei Cloud Developer Alliance
Oct 12, 2017 · Artificial Intelligence

Which Machine Learning Skills Will Be Most In‑Demand in the Next 3‑5 Years?

The article explains that industrial AI needs specialists who can apply machine‑learning models to specific domains, outlines essential fundamentals such as regression, classification, neural networks, data visualization, and unsupervised learning, and offers practical career advice for students and early‑career professionals seeking to transition into machine‑learning roles.

Data visualizationIndustrial AINeural Networks
0 likes · 11 min read
Which Machine Learning Skills Will Be Most In‑Demand in the Next 3‑5 Years?
Hujiang Technology
Hujiang Technology
Oct 11, 2017 · Artificial Intelligence

An Overview of Machine Learning and Deep Learning: Definitions, Core Concepts, and Typical Architectures

This article provides a comprehensive introduction to machine learning and deep learning, covering their definitions, differences, key concepts such as generalization, regularization, and overfitting, as well as typical algorithms and network architectures like CNN and RNN, illustrated with numerous diagrams.

AlgorithmsNeural Networksmachine learning
0 likes · 22 min read
An Overview of Machine Learning and Deep Learning: Definitions, Core Concepts, and Typical Architectures
Architects' Tech Alliance
Architects' Tech Alliance
Oct 10, 2017 · Artificial Intelligence

An Overview of a Three-Day Introductory TensorFlow Tutorial

This article introduces TensorFlow, its origins and capabilities, and summarizes a three‑day hands‑on tutorial covering installation, basic models, convolutional and recurrent neural networks, and practical code examples for deep learning practitioners.

AIDeep LearningTensorFlow
0 likes · 5 min read
An Overview of a Three-Day Introductory TensorFlow Tutorial
Huawei Cloud Developer Alliance
Huawei Cloud Developer Alliance
Oct 9, 2017 · Artificial Intelligence

A Pragmatic Roadmap to Master Machine Learning: Courses, Resources, and Tips

The author shares a step‑by‑step self‑learning plan for machine learning, covering essential linear‑algebra refreshers, foundational algorithm courses, hands‑on coding tutorials in MATLAB and Python, advanced deep‑learning studies with CS231n, and a curated list of reference links and GitHub notes.

Deep Learninglinear algebramachine learning
0 likes · 8 min read
A Pragmatic Roadmap to Master Machine Learning: Courses, Resources, and Tips
Tongcheng Travel Technology Center
Tongcheng Travel Technology Center
Sep 29, 2017 · Big Data

Evolution of Monitoring Architecture and Traffic Alert Algorithms at Tongcheng Travel

This article describes how Tongcheng Travel’s monitoring system evolved from a monolithic design to a distributed and big‑data‑based architecture, introducing real‑time processing with Storm, machine‑learning‑enhanced alerts, and a multivariate linear regression model that dramatically improves traffic anomaly detection accuracy.

Big DataReal-time Processingarchitecture evolution
0 likes · 10 min read
Evolution of Monitoring Architecture and Traffic Alert Algorithms at Tongcheng Travel
Architects' Tech Alliance
Architects' Tech Alliance
Sep 28, 2017 · Artificial Intelligence

Gartner 2017 Top 10 Strategic Technology Trends: AI, Smart Apps, IoT, VR/AR, Digital Twin, Blockchain and More

Gartner's 2017 report outlines ten strategic technology trends—including artificial intelligence, smart applications, intelligent objects, immersive VR/AR, digital twins, blockchain, conversational systems, mesh services, digital platforms, and adaptive security—that together drive an intelligence‑centric, digitally connected future for enterprises.

AIBlockchainDigital Twin
0 likes · 12 min read
Gartner 2017 Top 10 Strategic Technology Trends: AI, Smart Apps, IoT, VR/AR, Digital Twin, Blockchain and More
iQIYI Technical Product Team
iQIYI Technical Product Team
Sep 22, 2017 · Artificial Intelligence

iQIYI NLP Team: Research Topics, Progress, and Applications in Video Services

The iQIYI NLP team applies lexical analysis, knowledge‑graph construction, tag recommendation, query understanding, voice‑assistant semantics, sentiment mining, and box‑office/view‑count prediction—leveraging weakly labeled data, CRF/CNN‑CRF models and deep learning—to enhance video comprehension, recommendation, search and commercial services across the platform.

NLPRecommendation SystemsSpeech Assistant
0 likes · 13 min read
iQIYI NLP Team: Research Topics, Progress, and Applications in Video Services
Hujiang Technology
Hujiang Technology
Sep 20, 2017 · Artificial Intelligence

Fundamentals and Algorithms of Recommender Systems

This article explains why recommender systems were created, describes the problem of information overload, introduces core algorithms such as popularity, content‑based, collaborative filtering and hybrid methods, and illustrates each with a six‑user/book example and a Netflix case study.

collaborative filteringcontent-based filteringhybrid recommendation
0 likes · 17 min read
Fundamentals and Algorithms of Recommender Systems
Architecture Digest
Architecture Digest
Sep 15, 2017 · Artificial Intelligence

Overview of Recommendation Systems: Goals, Methods, Architecture, and Practical Considerations

This article explains the objectives of recommendation systems, compares popular recommendation approaches, details the components and algorithms of personalized recommendation pipelines, and discusses practical challenges such as real‑time processing, freshness, cold‑start, diversity, content quality, and surprise handling.

Real-Timecold startdata pipeline
0 likes · 15 min read
Overview of Recommendation Systems: Goals, Methods, Architecture, and Practical Considerations
JD Retail Technology
JD Retail Technology
Sep 13, 2017 · Artificial Intelligence

Machine Learning Applications for Product Data Quality and Knowledge Graph Construction at JD.com

At the 2nd China Big Data International Summit 2017, JD’s chief architect presented how machine‑learning techniques are applied across e‑commerce to improve product data quality, ensure compliance, resolve image‑text mismatches, automate category identification, restructure titles, and build a multi‑dimensional product knowledge graph.

Data QualityKnowledge Graphartificial intelligence
0 likes · 9 min read
Machine Learning Applications for Product Data Quality and Knowledge Graph Construction at JD.com
Alibaba Cloud Developer
Alibaba Cloud Developer
Aug 28, 2017 · Artificial Intelligence

Can Machine Learning Predict Baby Life Stages to Boost E‑Commerce Recommendations?

This paper introduces a dynamic fusion algorithm that leverages multi‑dimensional logistic regression and rich consumer behavior features to infer infants' life stages from parental e‑commerce actions, demonstrating significant accuracy improvements over memory‑less baselines across multiple months of Taobao data.

consumer behaviordynamic fusione‑commerce
0 likes · 13 min read
Can Machine Learning Predict Baby Life Stages to Boost E‑Commerce Recommendations?
Qunar Tech Salon
Qunar Tech Salon
Aug 22, 2017 · Artificial Intelligence

Sliding Window and SVM Based Web Crawler Detection System Design

This article describes a flexible web crawler identification approach that combines sliding‑window data collection with Support Vector Machine classification, detailing the underlying concepts, feature extraction, system architecture, client‑server interaction, and deployment steps for practical use.

Sliding WindowSystem Architectureclient-server
0 likes · 7 min read
Sliding Window and SVM Based Web Crawler Detection System Design
Efficient Ops
Efficient Ops
Aug 21, 2017 · Operations

How AI-Driven Automation Transforms Tencent Game Operations

This article explains how Tencent Game operations moved from manual, threshold‑based monitoring to an AI‑powered, data‑driven workflow that automates scaling, improves online‑curve monitoring, enables full‑dimensional analysis, and reduces time, labor, and cost while enhancing player experience.

AutomationGamingOperations
0 likes · 16 min read
How AI-Driven Automation Transforms Tencent Game Operations
Qunar Tech Salon
Qunar Tech Salon
Aug 21, 2017 · Artificial Intelligence

Tourism Comment Text Mining and Recommendation System Using NLP and Big Data

This article presents a comprehensive NLP‑driven text‑mining workflow for tourism comment data, covering data cleaning, word2vec training, keyword extraction, sentiment analysis, ranking, and a lightweight architecture that enables fast, accurate recommendation of scenic spots for users.

NLPSentiment Analysismachine learning
0 likes · 5 min read
Tourism Comment Text Mining and Recommendation System Using NLP and Big Data
Qunar Tech Salon
Qunar Tech Salon
Aug 16, 2017 · Artificial Intelligence

Applying Wide & Deep Learning to Meituan‑Dianping Recommendation System

This article describes how Meituan‑Dianping leverages deep learning, especially the Wide & Deep model, to improve its recommendation system by addressing business diversity, user context, feature engineering challenges, optimizer and loss function choices, and presents offline and online experimental results showing significant CTR gains.

CTRDeep LearningWide&Deep
0 likes · 22 min read
Applying Wide & Deep Learning to Meituan‑Dianping Recommendation System
Efficient Ops
Efficient Ops
Aug 9, 2017 · Artificial Intelligence

Can AI Predict Disk Failures? RGF + Transfer Learning for Reliable Data Centers

This article reviews a KDD 2016 study that combines the Regularized Greedy Forest algorithm with transfer learning to accurately predict hard‑disk failures in data centers, addressing challenges like irrelevant SMART attributes, imbalanced data, and model portability across disk models.

RGF algorithmSMART attributesdata center reliability
0 likes · 12 min read
Can AI Predict Disk Failures? RGF + Transfer Learning for Reliable Data Centers
21CTO
21CTO
Aug 8, 2017 · Artificial Intelligence

How to Transition from Programmer to Data Scientist: A Practical AI Roadmap

This guide outlines a step‑by‑step learning roadmap for ordinary programmers aiming to become data scientists, covering essential math, statistics, machine learning fundamentals, feature engineering, deep learning resources, open‑source tools, and practical project advice to navigate the AI field effectively.

AIData ScienceDeep Learning
0 likes · 18 min read
How to Transition from Programmer to Data Scientist: A Practical AI Roadmap
21CTO
21CTO
Aug 6, 2017 · Artificial Intelligence

How YouTube’s Recommendation Engine Evolved: From Graph Walks to Deep Neural Networks

This article reviews YouTube’s recommendation system research from 2008 to 2016, detailing four development stages—user‑video graph walks, video‑video graph walks, search‑based methods with collaborative filtering, and deep neural networks—highlighting key algorithms, system architectures, and experimental results.

Deep LearningSearchYouTube
0 likes · 17 min read
How YouTube’s Recommendation Engine Evolved: From Graph Walks to Deep Neural Networks
High Availability Architecture
High Availability Architecture
Jul 19, 2017 · Artificial Intelligence

Weiflow: A Scalable Machine Learning Workflow Framework for Sina Weibo

The article introduces Weiflow, a dual‑layer DAG‑based machine‑learning workflow framework designed for Sina Weibo, and explains how its modular XML configuration, Scala implementation, and integration with Spark, TensorFlow, Hive, Storm, and Flink improve development efficiency, scalability, and execution performance across the entire ML pipeline.

Big DataDAGScala
0 likes · 16 min read
Weiflow: A Scalable Machine Learning Workflow Framework for Sina Weibo
Alibaba Cloud Developer
Alibaba Cloud Developer
Jul 19, 2017 · Artificial Intelligence

How Alibaba’s CLOES Algorithm Cut Search Latency by 30% During Double‑11

Alibaba’s 2016 Double‑11 e‑commerce search team unveiled the CLOES cascade ranking algorithm, which reduces CPU usage by about 45%, lowers average search latency from 33 ms to 24 ms, and boosts GMV by nearly 1%, with detailed offline and online validation presented in a KDD‑2017 paper.

E-commerce SearchKDD 2017Performance Optimization
0 likes · 9 min read
How Alibaba’s CLOES Algorithm Cut Search Latency by 30% During Double‑11
Alibaba Cloud Developer
Alibaba Cloud Developer
Jul 17, 2017 · Artificial Intelligence

How Alibaba Turns Big Data into ‘Data New Energy’ with Automated Tagging and Distributed Knowledge Graphs

Alibaba's senior algorithm expert Yang Hongxia explains how the company fuses massive, heterogeneous data sources into a unified platform, builds automated tag‑production pipelines and large‑scale distributed knowledge graphs, and applies these technologies to drive smarter business decisions and AI‑enabled services.

AlibabaBig DataData Platform
0 likes · 14 min read
How Alibaba Turns Big Data into ‘Data New Energy’ with Automated Tagging and Distributed Knowledge Graphs
High Availability Architecture
High Availability Architecture
Jul 12, 2017 · Artificial Intelligence

Machine Learning Platform and Risk‑Control Applications at DianRong Net

The article presents a comprehensive overview of DianRong Net's in‑house machine‑learning platform built on Spark, its workflow, pain points it addresses, risk‑control case studies using graph mining, and practical tips for improving model performance through data, algorithms, hyper‑parameter tuning and ensemble methods.

Big DataModel OptimizationSpark
0 likes · 14 min read
Machine Learning Platform and Risk‑Control Applications at DianRong Net
Architects' Tech Alliance
Architects' Tech Alliance
Jul 7, 2017 · Artificial Intelligence

Understanding Business Intelligence (BI) and Artificial Intelligence (AI): Definitions, Differences, and Real‑World Applications

The article explains Gartner’s definitions of Business Intelligence and Artificial Intelligence, compares their core capabilities, discusses whether AI is over‑hyped, and illustrates how AI‑driven solutions differ from traditional BI across marketing, public safety, finance, and education sectors.

BIBusiness IntelligenceData Analytics
0 likes · 12 min read
Understanding Business Intelligence (BI) and Artificial Intelligence (AI): Definitions, Differences, and Real‑World Applications
Tencent Advertising Technology
Tencent Advertising Technology
Jul 3, 2017 · Artificial Intelligence

Tencent Social Advertising College Algorithm Contest

Tencent's social advertising team hosts an algorithm contest for college students, leveraging big data and machine learning to develop innovative solutions for social advertising scenarios, inviting participants to submit algorithmic approaches to real-world advertising challenges.

Academic CompetitionAlgorithm ContestBig Data
0 likes · 2 min read
Tencent Social Advertising College Algorithm Contest
21CTO
21CTO
Jun 29, 2017 · Artificial Intelligence

Why Machine Learning Mirrors Human Learning: From Features to Reinforcement

The article explores how machine learning models emulate human learning by converting diverse real‑world descriptions into numerical features, illustrating concepts such as one‑hot encoding, supervised, unsupervised, and reinforcement learning, and emphasizing the importance of mapping inputs to outputs for intelligent systems.

AI conceptsfeaturesmachine learning
0 likes · 14 min read
Why Machine Learning Mirrors Human Learning: From Features to Reinforcement
21CTO
21CTO
Jun 28, 2017 · Artificial Intelligence

How Ordinary Programmers Can Seamlessly Transition into AI: A Practical Roadmap

This guide outlines a smooth, step‑by‑step learning path for busy programmers with a bachelor's degree, covering AI fundamentals, essential mathematics, recommended courses, practical projects, deep‑learning resources, open‑source tools, and strategies to stay motivated and succeed in the field.

AI transitiondeep learning resourceslearning roadmap
0 likes · 15 min read
How Ordinary Programmers Can Seamlessly Transition into AI: A Practical Roadmap
Alibaba Cloud Developer
Alibaba Cloud Developer
Jun 27, 2017 · Artificial Intelligence

How Alibaba’s OCPC Algorithm Boosts ROI and Platform Revenue in Taobao Ads

The paper “Optimized Cost per Click in Taobao Display Advertising” introduces a novel two‑level OCPC smart bidding algorithm that jointly optimizes advertiser ROI, user experience, and platform revenue, presents detailed mathematical formulations, offline and online experiments showing significant gains in GMV, CTR, CVR, and RPM across single‑item and banner ad placements.

OCPCROI optimizationTaobao
0 likes · 11 min read
How Alibaba’s OCPC Algorithm Boosts ROI and Platform Revenue in Taobao Ads
Tencent Advertising Technology
Tencent Advertising Technology
Jun 25, 2017 · Artificial Intelligence

Interview with ‘拔萝卜’: Lessons Learned from the Tencent Social Ads Algorithm Competition

In this interview, a solo female participant from Shanghai Jiao Tong University shares her experience, challenges, and technical insights—including feature engineering, memory management, and model tuning with XGBoost and LightGBM—gained while competing in the Tencent Social Ads algorithm contest.

Model tuningTencentXGBoost
0 likes · 5 min read
Interview with ‘拔萝卜’: Lessons Learned from the Tencent Social Ads Algorithm Competition
Baidu Intelligent Testing
Baidu Intelligent Testing
Jun 20, 2017 · Big Data

Design and Challenges of Web Crawlers and Link Scheduling for Knowledge Graph Construction

The article explains how web crawlers (spiders) collect data for knowledge graphs, covering core tasks, major challenges, crawler features, new‑link expansion, storage design, link‑selection scheduling strategies, and the role of large‑scale data mining and machine learning in optimizing crawl efficiency.

Big DataKnowledge GraphSpider
0 likes · 17 min read
Design and Challenges of Web Crawlers and Link Scheduling for Knowledge Graph Construction
21CTO
21CTO
Jun 20, 2017 · Artificial Intelligence

How Toutiao’s AI Powers Personalized News Recommendations

This article examines Toutiao’s rapid rise as a personalized news platform, detailing its AI‑driven recommendation pipeline, web‑crawling infrastructure, similarity‑matrix algorithms, A/B testing, and the role of human moderation in delivering highly targeted content to billions of users.

A/B testingAIBig Data
0 likes · 16 min read
How Toutiao’s AI Powers Personalized News Recommendations
21CTO
21CTO
Jun 16, 2017 · Fundamentals

11 Bold Predictions Shaping the Future of Programming

This article surveys eleven forward‑looking predictions—from cloud computing eclipsing Moore's law to IoT security challenges, video‑centric web experiences, AI‑driven features, evolving UI design, autonomous transport, legal constraints, and the rise of containers—highlighting how programmers must adapt to stay competitive.

IoT securitycloud computingfuture technology
0 likes · 12 min read
11 Bold Predictions Shaping the Future of Programming
Meituan Technology Team
Meituan Technology Team
Jun 16, 2017 · Artificial Intelligence

Evolution of Meituan Travel Search Recall Strategies

Meituan‑Dianping’s travel search team tackles cross‑region queries and noisy data by iteratively refining a four‑step, case‑driven pipeline that classifies intent, segments queries, ranks results with distance and term‑importance models, and employs multi‑stage, parallel recall to steadily boost purchase rate, CTR, and user satisfaction.

SearchTravelintent classification
0 likes · 20 min read
Evolution of Meituan Travel Search Recall Strategies
Alibaba Cloud Developer
Alibaba Cloud Developer
Jun 15, 2017 · Artificial Intelligence

How Alibaba’s Mixed Logistic Regression Revolutionizes CTR Prediction

This article explains the technical background of click‑through‑rate (CTR) prediction, critiques traditional linear models, introduces Alibaba’s Mixed Logistic Regression (MLR) algorithm with its advanced features and large‑scale distributed implementation, and reviews its successful deployment and remaining challenges in advertising systems.

AdvertisingCTR predictionMLR
0 likes · 13 min read
How Alibaba’s Mixed Logistic Regression Revolutionizes CTR Prediction
Suning Technology
Suning Technology
Jun 9, 2017 · Big Data

How Suning’s AI‑Powered Smart Replenishment Turns Retail from B2C to C2B

Suning’s smart replenishment system showcased at CES Asia 2017 leverages big‑data analytics and machine‑learning models—linear regression, random forest, and XGBoost—to predict sales, optimize inventory across multiple warehouses, and shift retail from traditional B2C to a data‑driven C2B approach.

Big Datainventory optimizationmachine learning
0 likes · 5 min read
How Suning’s AI‑Powered Smart Replenishment Turns Retail from B2C to C2B
Tencent IMWeb Frontend Team
Tencent IMWeb Frontend Team
May 28, 2017 · Artificial Intelligence

This Week’s Tech Highlights: AlphaGo’s Farewell, AI Advances & Git Security

The weekly roundup covers AlphaGo’s retirement and release of self‑play games, Tencent’s surge as Asia’s top startup investor, Microsoft’s migration of Windows code to Git, WeChat mini‑program enhancements, Alibaba’s retail partnership, AI insights from Siri’s co‑founder and Facebook’s new NMT model, Xamarin Live Player’s impact, and Git 2.13 security improvements.

Securitymachine learningsoftware development
0 likes · 10 min read
This Week’s Tech Highlights: AlphaGo’s Farewell, AI Advances & Git Security
Qunar Tech Salon
Qunar Tech Salon
May 15, 2017 · Artificial Intelligence

Building an Algorithm Platform for Machine Learning Deployment at Qunar

The article describes how a three‑stage algorithm platform was designed and implemented to automate model deployment, unify feature processing, and provide service‑oriented model evaluation, debugging, and monitoring for machine‑learning applications in a large e‑commerce environment.

AI servicesAlgorithm PlatformJava
0 likes · 10 min read
Building an Algorithm Platform for Machine Learning Deployment at Qunar
MaGe Linux Operations
MaGe Linux Operations
May 11, 2017 · Artificial Intelligence

Essential Math Foundations for AI: Linear Algebra, Probability & More

The article reviews the surge of AI interest sparked by AlphaGo and Master, explains why strong mathematics—especially linear algebra, probability, statistics, calculus, and optimization—is crucial for AI practitioners, and provides curated free online courses, textbooks, and resources to help beginners master these subjects.

AIResourceslinear algebra
0 likes · 14 min read
Essential Math Foundations for AI: Linear Algebra, Probability & More
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 DevelopmentContestData Science Competition
0 likes · 3 min read
JD Data Algorithm Competition: Solving Shopping Dilemmas with AI
Tencent Advertising Technology
Tencent Advertising Technology
May 9, 2017 · Artificial Intelligence

Kaggle Competition Overview and Practical Guide for Data Mining

This article provides a comprehensive introduction to Kaggle, covering its history, competition formats, participation rules, public and private leaderboard mechanics, and a step‑by‑step workflow that includes data analysis, cleaning, feature engineering, model training, validation, hyper‑parameter tuning, ensemble techniques, and automation frameworks for successful data‑mining contests.

Kagglefeature engineeringmachine learning
0 likes · 24 min read
Kaggle Competition Overview and Practical Guide for Data Mining
Meituan Technology Team
Meituan Technology Team
May 5, 2017 · Artificial Intelligence

Meituan DSP Strategy: Real‑time Bidding, Recall, CTR and Value Prediction

Meituan’s demand‑side platform combines real‑time bidding with a two‑service architecture—RecServer for multi‑scenario ad recall and PredictorServer for CTR and conversion‑value prediction—leveraging behavior, location, collaborative‑filtering and matrix‑factorization features, logistic‑regression and GBDT models, and continuous A/B and metric monitoring to optimize ROI.

AdvertisingDSPmachine learning
0 likes · 20 min read
Meituan DSP Strategy: Real‑time Bidding, Recall, CTR and Value Prediction
360 Zhihui Cloud Developer
360 Zhihui Cloud Developer
May 4, 2017 · Artificial Intelligence

Master Linear, Weighted, and Ridge Regression: Theory, Code, and Evaluation

This article introduces regression concepts, explains linear, locally weighted, and ridge regression methods, demonstrates their mathematical foundations, provides Python implementations, and discusses model evaluation techniques to help readers choose the appropriate regression approach for their data.

linear regressionmachine learningregression
0 likes · 10 min read
Master Linear, Weighted, and Ridge Regression: Theory, Code, and Evaluation
Alibaba Cloud Developer
Alibaba Cloud Developer
Apr 28, 2017 · Artificial Intelligence

How Alibaba’s AI‑Powered Design Platform “Luban” Revolutionizes Mass Creative Production

Alibaba unveiled its AI‑driven design platform Luban, which leverages massive data and machine‑learning algorithms to automatically generate high‑quality, personalized graphics at double‑digit scale, reshaping design workflows, boosting efficiency, and prompting a strategic shift for designers in the new commercial era.

AI designAlibabaDesign Automation
0 likes · 7 min read
How Alibaba’s AI‑Powered Design Platform “Luban” Revolutionizes Mass Creative Production
21CTO
21CTO
Apr 20, 2017 · Artificial Intelligence

How Facebook Evaluates Its Newsfeed Recommendations: Metrics, Models, and User Surveys

Facebook evaluates its Newsfeed recommendation quality through three pillars—machine-learning model metrics like AUC, extensive product data KPIs such as DAU and interaction rates, and user-survey feedback—while maintaining long-term backtests and emphasizing the risks of relying on a single metric.

A/B testingKPIRecommendation Systems
0 likes · 7 min read
How Facebook Evaluates Its Newsfeed Recommendations: Metrics, Models, and User Surveys
Architects' Tech Alliance
Architects' Tech Alliance
Apr 18, 2017 · Artificial Intelligence

A Visual Journey Through the Evolution of Artificial Intelligence

This article defines artificial intelligence as a branch of computer science that aims to simulate and extend human intelligence, outlines its key research areas such as robotics and natural language processing, and presents a detailed visual timeline from TalkingData that charts the technology’s major milestones.

AI historyartificial intelligencecomputer science
0 likes · 2 min read
A Visual Journey Through the Evolution of Artificial Intelligence
21CTO
21CTO
Apr 17, 2017 · Artificial Intelligence

Can Neural Networks Write Other Neural Networks? Inside the Neural Complete Project

Neural Complete, an open‑source project by Pascal van Kooten, trains a neural network to auto‑complete the code of another neural network using LSTM and Keras, demonstrating AI‑driven metaprogramming that could accelerate software development, research, and numerous future applications.

AI programmingDeep LearningNeural Networks
0 likes · 6 min read
Can Neural Networks Write Other Neural Networks? Inside the Neural Complete Project
MaGe Linux Operations
MaGe Linux Operations
Apr 7, 2017 · Artificial Intelligence

Predict Diabetes with Linear Regression: A Step‑by‑Step Python Guide

This tutorial walks through using scikit‑learn's LinearRegression on the classic diabetes dataset, covering data description, model training with fit(), making predictions, evaluating performance, and code optimizations, all illustrated with clear output images and plots.

Diabetes PredictionPythonlinear regression
0 likes · 5 min read
Predict Diabetes with Linear Regression: A Step‑by‑Step Python Guide
Meitu Technology
Meitu Technology
Apr 6, 2017 · Artificial Intelligence

Meipai Text Matters: Mining and Practice of Community Text

The talk demonstrates how Meipai, a leading Chinese short‑video community, leverages large‑scale text mining and machine‑learning techniques—ranging from anti‑spam filtering to AI‑enhanced search—to enrich captions, comments, and metadata, improve user experience, and inspire further research on text data in video platforms.

Community analysisanti-spammachine learning
0 likes · 2 min read
Meipai Text Matters: Mining and Practice of Community Text
Meitu Technology
Meitu Technology
Apr 6, 2017 · Artificial Intelligence

Meitu Internet Technology Salon: AI and Machine Learning Applications in Practice

The fourth Meitu Internet Technology Salon showcased practical AI and machine learning uses, highlighting Meipai’s text‑anti‑spam, hot‑topic detection, sentiment analysis and personalized video search, while Baidu demonstrated ML‑driven business intelligence tools for multi‑source data mining, user profiling, and intelligent enterprise and HR management.

Business IntelligenceSentiment Analysisanti-spam
0 likes · 7 min read
Meitu Internet Technology Salon: AI and Machine Learning Applications in Practice
21CTO
21CTO
Apr 4, 2017 · Artificial Intelligence

How Vipshop Evolved Its Real-Time Personalized Recommendation Engine

This article recounts Wu Guanlin’s presentation on the evolution of Vipshop’s personalized recommendation system, detailing the technical challenges of real‑time predictions, the three generations of architecture, the four‑stage recommendation engine, and the VRE platform’s design for scalability and low latency.

Big DataSystem Architecturemachine learning
0 likes · 10 min read
How Vipshop Evolved Its Real-Time Personalized Recommendation Engine
21CTO
21CTO
Apr 1, 2017 · Artificial Intelligence

How Modern Apps Use AI to Personalize Your Content Feed

The article explores how recommendation technologies powered by machine learning permeate everyday platforms—from e‑commerce and video services to social media and news apps—detailing the data they collect, the algorithms they employ, and the limits of personalization in unpredictable human scenarios.

Recommendation Systemscontent filteringmachine learning
0 likes · 7 min read
How Modern Apps Use AI to Personalize Your Content Feed
Meituan Technology Team
Meituan Technology Team
Mar 24, 2017 · Artificial Intelligence

Tourism Recommendation System: Strategy Iterations, Architecture, and Future Challenges

The article outlines Meituan‑Dianping’s tourism recommendation system, detailing its evolution from simple hot‑sale recall to sophisticated decay‑based, GPS‑aware, collaborative filtering and XGBoost reranking pipelines, the four‑layer architecture supporting dozens of travel scenarios, and future plans to broaden recall, adopt deep models, and expand multimodal travel recommendations.

Big DataTourismarchitecture
0 likes · 26 min read
Tourism Recommendation System: Strategy Iterations, Architecture, and Future Challenges
Alibaba Cloud Developer
Alibaba Cloud Developer
Mar 16, 2017 · Artificial Intelligence

How Alibaba Harnesses Deep Reinforcement Learning for E‑Commerce Innovation

This interview with Alibaba researcher Xu Yinghui reveals how the company built large‑scale deep reinforcement learning systems for search, recommendation, logistics and online advertising, detailing team structures, technical breakthroughs, training challenges, and future directions such as multi‑agent learning and GAN integration.

AIAlibabaDeep Learning
0 likes · 20 min read
How Alibaba Harnesses Deep Reinforcement Learning for E‑Commerce Innovation
Qunar Tech Salon
Qunar Tech Salon
Mar 12, 2017 · Big Data

Essential Skills and Career Paths for Data Professionals: From Big Data Platforms to AI

The article outlines the key competencies, responsibilities, and career development advice for data professionals across the entire data stack—from building big‑data platforms and data warehouses to visualization, analysis, algorithm engineering, and deep‑learning applications—emphasizing the importance of creating business value with data.

Big DataData AnalystData Warehouse
0 likes · 15 min read
Essential Skills and Career Paths for Data Professionals: From Big Data Platforms to AI
MaGe Linux Operations
MaGe Linux Operations
Mar 3, 2017 · Artificial Intelligence

Top 5 Python Libraries to Supercharge Your Machine Learning Projects

This article introduces five highly rated Python libraries—PyWren, Tfdeploy, Luigi, Kubelib, and PyTorch—that streamline data handling, cloud execution, workflow orchestration, and GPU acceleration, helping machine‑learning engineers boost productivity and tackle complex projects more efficiently.

AWS LambdaKubernetesPyTorch
0 likes · 6 min read
Top 5 Python Libraries to Supercharge Your Machine Learning Projects
21CTO
21CTO
Mar 2, 2017 · Artificial Intelligence

How User Personas Power Modern Recommendation Systems: From Theory to NetEase Yanxuan

This article explains the concept and construction of user personas, explores the essence and algorithms of recommendation systems, compares movie and e‑commerce scenarios, and details NetEase Yanxuan's practical CTR‑based recommendation model with extensive feature engineering.

Recommendation Systemse‑commercefeature engineering
0 likes · 13 min read
How User Personas Power Modern Recommendation Systems: From Theory to NetEase Yanxuan
Nightwalker Tech
Nightwalker Tech
Mar 2, 2017 · Information Security

Techniques and Tools for Anti‑Spam Content Filtering in PHP

The discussion outlines practical anti‑spam strategies—including text length limits, keyword replacement, trie‑based data structures, AC automata, Bayesian and vector‑similarity algorithms, and PHP extensions such as libdatrie—while also sharing performance metrics and resource links for implementing robust content filtering systems.

PHPTriecontent filtering
0 likes · 4 min read
Techniques and Tools for Anti‑Spam Content Filtering in PHP
MaGe Linux Operations
MaGe Linux Operations
Feb 28, 2017 · Artificial Intelligence

Top 16 Python Machine Learning Libraries You Should Know

This article provides a concise overview of sixteen popular Python machine‑learning libraries—including scikit‑learn, NLTK, Theano, and Orange—detailing their main features, typical use cases, and where to find their project pages, making it a handy reference for data‑science practitioners.

Data SciencePythonartificial intelligence
0 likes · 14 min read
Top 16 Python Machine Learning Libraries You Should Know
MaGe Linux Operations
MaGe Linux Operations
Feb 28, 2017 · Artificial Intelligence

How to Build a Python Machine Learning Environment and Fit Your First Model

This tutorial walks through setting up a Python 2.7 machine learning environment with scikit-learn, installing required libraries, loading web traffic data, cleaning NaN entries, visualizing the data, performing a linear regression using SciPy's polyfit, and evaluating the model's fit.

Data visualizationPythonlinear regression
0 likes · 9 min read
How to Build a Python Machine Learning Environment and Fit Your First Model
Nightwalker Tech
Nightwalker Tech
Feb 27, 2017 · Big Data

Community Discussion on Learning Paths, Tools, and Applications in Big Data

A diverse group of practitioners share recommendations for books, technologies, real‑world use cases, and practical challenges when learning and applying big‑data processing, covering Hadoop, Spark, data visualization, ETL, and the relationship between data, algorithms, and business value.

Big DataHadoopdata analysis
0 likes · 16 min read
Community Discussion on Learning Paths, Tools, and Applications in Big Data
Alibaba Cloud Developer
Alibaba Cloud Developer
Feb 27, 2017 · Artificial Intelligence

Essential Machine Learning Algorithms Every Beginner Must Know

This guide introduces beginners to core machine learning concepts, covering feature design, supervised and unsupervised methods such as perceptron, logistic regression, decision trees, LDA, and ensemble techniques like bagging and boosting, while explaining model evaluation, overfitting, and practical optimization strategies.

Model EvaluationUnsupervised Learningensemble methods
0 likes · 9 min read
Essential Machine Learning Algorithms Every Beginner Must Know
Alibaba Cloud Developer
Alibaba Cloud Developer
Feb 24, 2017 · Artificial Intelligence

Alibaba’s Reinforcement Learning Boost for E‑Commerce Search & Recommendations

Alibaba leveraged reinforcement learning, highlighted by MIT Technology Review’s 2017 breakthrough list, to transform its e‑commerce search and recommendation systems during Double 11, deploying large‑scale online and batch training pipelines, dynamic market segmentation, and real‑time decision models that boosted click‑through rates by up to 20 %.

e‑commercemachine learningonline training
0 likes · 14 min read
Alibaba’s Reinforcement Learning Boost for E‑Commerce Search & Recommendations
Alibaba Cloud Developer
Alibaba Cloud Developer
Feb 20, 2017 · Artificial Intelligence

How Alibaba’s Graph Embedding Boosts E‑Commerce Recommendations by 60%

Alibaba’s merchant division introduced a scalable graph‑embedding approach for its “thousands‑of‑people‑one‑face” recommendation module, enabling personalized product suggestions within sparse shop data, improving click‑through rates by 30% and conversions by 60%, and presenting theoretical insights validated at AAAI 2017.

e‑commercegraph embeddingmachine learning
0 likes · 13 min read
How Alibaba’s Graph Embedding Boosts E‑Commerce Recommendations by 60%
Meituan Technology Team
Meituan Technology Team
Feb 17, 2017 · Big Data

User Profiling and Machine Learning Practices for Food Delivery O2O Platforms

Meituan Delivery’s rapid expansion across multiple categories relies on detailed user profiling and machine‑learning models—such as high‑potential customer prediction, churn risk regression and Cox survival analysis—to personalize acquisition, retention, and scenario‑based cross‑selling, while addressing sparse behavior, unstructured data, and geographic context challenges.

Big DataO2Ochurn prediction
0 likes · 13 min read
User Profiling and Machine Learning Practices for Food Delivery O2O Platforms
Qunar Tech Salon
Qunar Tech Salon
Jan 24, 2017 · Artificial Intelligence

Practical Approaches to Deploying Machine Learning Models: Real‑time SOA, PMML, Rserve, and Spark

This article shares practical engineering experiences for deploying machine learning models in various scenarios—real‑time low‑volume predictions via Rserve or Python‑httpserve, high‑throughput real‑time serving with PMML‑wrapped Java classes, and offline batch predictions using simple shell scripts—detailing tools, performance considerations, and implementation steps.

Model DeploymentPMMLPython
0 likes · 11 min read
Practical Approaches to Deploying Machine Learning Models: Real‑time SOA, PMML, Rserve, and Spark
Ctrip Technology
Ctrip Technology
Jan 22, 2017 · Artificial Intelligence

Cross-Domain Recommendation: Concepts, Methods, and Novel Approaches

This article reviews the fundamentals of cross-domain recommendation, explains the limitations of single‑domain personalized recommendation, surveys existing collaborative‑filtering, transfer‑learning, and knowledge‑based methods, and introduces two novel tensor‑factorization and bilinear multilevel models that achieve superior performance on real datasets.

collaborative filteringcross-domain recommendationknowledge-based recommendation
0 likes · 17 min read
Cross-Domain Recommendation: Concepts, Methods, and Novel Approaches
Alibaba Cloud Developer
Alibaba Cloud Developer
Jan 20, 2017 · Artificial Intelligence

How E‑Commerce Giants Leverage Recommendation Algorithms – Insights from Xavier Amatriain

An illustrated guide explores the recommendation algorithms powering e‑commerce platforms, drawing on Xavier Amatriain’s CMU Machine Learning summer school lectures to explain collaborative filtering, content‑based, and hybrid approaches, their practical implementations, and the impact on user experience and sales.

Xavier Amatriaincollaborative filteringe‑commerce
0 likes · 4 min read
How E‑Commerce Giants Leverage Recommendation Algorithms – Insights from Xavier Amatriain
Ctrip Technology
Ctrip Technology
Jan 5, 2017 · Artificial Intelligence

Design and Implementation of a Billion‑Scale Generalized Recommendation System at Tencent Cloud

This article explains how Tencent built a billion‑scale, generalized recommendation system by designing a reusable algorithm library, deploying a low‑latency, highly available real‑time streaming platform (R2), and offering a cloud‑based recommendation engine that simplifies integration for internet businesses.

AIReal‑Time Computingcloud computing
0 likes · 11 min read
Design and Implementation of a Billion‑Scale Generalized Recommendation System at Tencent Cloud
Ctrip Technology
Ctrip Technology
Jan 5, 2017 · Artificial Intelligence

Practical Approaches to Deploying Machine Learning Models: PMML, Rserve, and Spark in Production

This article shares practical engineering experiences for deploying machine learning models in production, covering three typical scenarios—real‑time small data, real‑time large data, and offline predictions—and detailing how to use PMML, Rserve, Spark, shell scripts, and related tools to meet performance and operational requirements.

Model DeploymentPMMLRserve
0 likes · 12 min read
Practical Approaches to Deploying Machine Learning Models: PMML, Rserve, and Spark in Production
Hulu Beijing
Hulu Beijing
Dec 21, 2016 · Artificial Intelligence

Inside NIPS 2016: Highlights, Papers, and Insights from Hulu’s Researchers

The article offers a comprehensive overview of the 2016 NIPS conference in Barcelona, detailing its history, attendance, Hulu’s contributions as presenters and reviewers, key tutorials, invited talks, award-winning papers, symposium highlights, and the broader impact of deep learning and AI advancements.

AI ConferenceBest PapersDeep Learning
0 likes · 12 min read
Inside NIPS 2016: Highlights, Papers, and Insights from Hulu’s Researchers
Alibaba Cloud Infrastructure
Alibaba Cloud Infrastructure
Dec 17, 2016 · Artificial Intelligence

Understanding Voiceprint Recognition: Principles, Techniques, and Applications

The article explains voiceprint (speaker) recognition technology, covering its biological basis, 1:1 verification versus 1:N identification, content‑related versus content‑independent approaches, key acoustic features such as MFCC, the iVector framework, system workflow diagrams, and its use in an Alibaba security challenge.

Biometricsmachine learningspeaker verification
0 likes · 10 min read
Understanding Voiceprint Recognition: Principles, Techniques, and Applications
High Availability Architecture
High Availability Architecture
Dec 11, 2016 · Artificial Intelligence

Why Machine Learning Is Hard: Debugging Challenges and Exponential Difficulty

The article explains that while machine learning has advanced with abundant courses, textbooks, and frameworks, engineers still face hard debugging problems due to algorithmic, implementation, data, and model dimensions, leading to exponential difficulty and long feedback loops that demand intuition and systematic testing.

DebuggingModel TrainingSoftware Engineering
0 likes · 8 min read
Why Machine Learning Is Hard: Debugging Challenges and Exponential Difficulty
Meituan Technology Team
Meituan Technology Team
Dec 9, 2016 · Artificial Intelligence

A General Feature Production Framework for Meituan Delivery Ranking System

The paper presents a generic feature‑production framework for Meituan’s food‑delivery ranking system that abstracts statistical feature generation, storage, retrieval, and online loading into configurable dimensions, metrics and operators, enabling developers to add new features with minimal code and dramatically speeding up machine‑learning model iteration.

KV Storefeature engineeringmachine learning
0 likes · 12 min read
A General Feature Production Framework for Meituan Delivery Ranking System
Alibaba Cloud Developer
Alibaba Cloud Developer
Dec 8, 2016 · Artificial Intelligence

How AI Powers Data‑Driven Merchant Success

In this Alibaba Tech Forum talk, senior expert Wei Hu explains how machine learning and big‑data technologies are used to empower merchants with personalized storefronts, intelligent posters, and AI‑driven headlines, boosting their efficiency and sales performance.

AIAlibabaBig Data
0 likes · 2 min read
How AI Powers Data‑Driven Merchant Success
Alibaba Cloud Developer
Alibaba Cloud Developer
Dec 7, 2016 · Artificial Intelligence

How Online AI Transforms Search and Recommendation Systems

At Alibaba's 2016 Double 11 Tech Forum, researcher Xu Yinghui presented how online AI technologies enhance search and recommendation on the e‑commerce platform, turning massive user behavior data into actionable insights that improve traffic allocation and maximize welfare for consumers, sellers, and the platform.

AIAlibabaSearch
0 likes · 2 min read
How Online AI Transforms Search and Recommendation Systems
Ctrip Technology
Ctrip Technology
Dec 2, 2016 · Big Data

Design and Architecture of Ctrip's Aegis Risk Control System

This article presents a comprehensive overview of Ctrip's Aegis risk control system, detailing its modular architecture, rule engine, data service layer, Chloro analytics platform, and future directions, while highlighting the use of streaming, big‑data processing, and machine‑learning models for real‑time fraud detection.

Big DataReal-time Processingmachine learning
0 likes · 13 min read
Design and Architecture of Ctrip's Aegis Risk Control System
Architects' Tech Alliance
Architects' Tech Alliance
Nov 24, 2016 · Big Data

Data Mining Overview: Process, Techniques, and Model Evaluation

This article provides a comprehensive introduction to data mining, covering its definition, goal setting, data sampling, exploration, preprocessing, pattern discovery, model building, evaluation methods, and the main analytical techniques such as classification, regression, clustering, association rules, feature and deviation analysis, and web mining.

Model Evaluationassociation rulesclassification
0 likes · 10 min read
Data Mining Overview: Process, Techniques, and Model Evaluation
AI Large-Model Wave and Transformation Guide
AI Large-Model Wave and Transformation Guide
Nov 23, 2016 · Artificial Intelligence

How to Progress from Beginner to Expert in Machine Learning: A Four‑Stage Roadmap

This article outlines a four‑stage learning pathway for programmers—from initial exposure to advanced mastery—detailing the goals, recommended resources, and practical activities for each phase, helping readers identify their current level and plan concrete steps toward becoming proficient in machine learning.

AI educationCareer Developmentbeginner guide
0 likes · 11 min read
How to Progress from Beginner to Expert in Machine Learning: A Four‑Stage Roadmap
21CTO
21CTO
Nov 6, 2016 · Artificial Intelligence

How to Build a Scalable AI-Powered Recommendation System with SOA

This article outlines a service‑oriented architecture for a high‑availability personalized recommendation platform, detailing the front‑end, back‑end, crawler, user‑profile modeling, data collection from logs and client events, and processing pipelines using technologies such as Node.js, Python, RabbitMQ/Kafka, MongoDB and TensorFlow.

SOATensorFlowdata pipeline
0 likes · 5 min read
How to Build a Scalable AI-Powered Recommendation System with SOA