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DataFunTalk
DataFunTalk
Feb 15, 2024 · Big Data

Data Quality Review: From Compliance to Reasonableness and Toolchain Overview

This article explores data collection governance by distinguishing compliance from reasonableness, introduces a comprehensive quality review tool system—including visual inspection, intelligent judgement, and self‑diagnosis—details key techniques such as comparison operators and sampling, and outlines a three‑layer architecture and future directions for data quality assurance.

Big DataData Governancedata sampling
0 likes · 18 min read
Data Quality Review: From Compliance to Reasonableness and Toolchain Overview
Model Perspective
Model Perspective
Mar 19, 2023 · Artificial Intelligence

Master Data Sampling Techniques in Python for Machine Learning

This article explains common data sampling methods—random, stratified, oversampling, undersampling, and adaptive sampling—and provides Python code examples using scikit-learn and imbalanced-learn to implement each technique on the Iris dataset and synthetic data.

data samplingoversamplingscikit-learn
0 likes · 11 min read
Master Data Sampling Techniques in Python for Machine Learning
DataFunTalk
DataFunTalk
Dec 28, 2021 · Artificial Intelligence

Evaluation Framework and Methodology for OPPO XiaoBu AI Assistant

This article presents a comprehensive evaluation framework for OPPO's XiaoBu AI assistant, covering evaluation concepts, objectives, five key elements, sampling methods, dimension selection, annotation scoring, report generation, and a detailed Q&A that illustrates practical metrics and processes for voice and search services.

AI EvaluationMetricsOPPO
0 likes · 23 min read
Evaluation Framework and Methodology for OPPO XiaoBu AI Assistant
DataFunSummit
DataFunSummit
Dec 27, 2021 · Artificial Intelligence

Evaluation Framework and Methodology for OPPO XiaoBu AI Assistant

This article presents a comprehensive evaluation framework for OPPO's XiaoBu AI assistant, covering the concept and purpose of evaluation, the five key evaluation elements, data sampling strategies, dimension and rule selection, annotation scoring, reporting guidelines, and detailed procedures for assessing wake‑up, ASR, NLU, and TTS performance.

AI EvaluationMetricsReporting
0 likes · 20 min read
Evaluation Framework and Methodology for OPPO XiaoBu AI Assistant
HomeTech
HomeTech
Feb 28, 2019 · Artificial Intelligence

How to Systematically Test and Monitor AI Models in Large‑Scale Production

This article presents a comprehensive approach to testing, automating, and monitoring AI prediction models in a high‑traffic environment, covering background, challenges, evaluation metrics, data sampling methods, automated test scripts, and online monitoring to ensure model accuracy, performance, and reliability.

AI testingAutomationBig Data
0 likes · 13 min read
How to Systematically Test and Monitor AI Models in Large‑Scale Production
Tencent Advertising Technology
Tencent Advertising Technology
Jun 14, 2017 · Big Data

Techniques for Handling Large-Scale Competition Data: Sampling, Feature Processing, and External‑Memory Learning

This article presents practical strategies for processing massive competition datasets—including down‑sampling, streaming feature extraction, external‑memory learning, and tool recommendations—to overcome memory constraints and improve model building efficiency.

Online Learningdata samplingexternal memory learning
0 likes · 4 min read
Techniques for Handling Large-Scale Competition Data: Sampling, Feature Processing, and External‑Memory Learning