[[["わかりやすい","easyToUnderstand","thumb-up"],["問題の解決に役立った","solvedMyProblem","thumb-up"],["その他","otherUp","thumb-up"]],[["必要な情報がない","missingTheInformationINeed","thumb-down"],["複雑すぎる / 手順が多すぎる","tooComplicatedTooManySteps","thumb-down"],["最新ではない","outOfDate","thumb-down"],["翻訳に関する問題","translationIssue","thumb-down"],["サンプル / コードに問題がある","samplesCodeIssue","thumb-down"],["その他","otherDown","thumb-down"]],["最終更新日 2025-07-27 UTC。"],[[["This course explores common data traps encountered in machine learning, encompassing dataset quality, thinking processes, visualization, and statistical analysis."],["Machine learning practitioners must critically assess their datasets, identifying potential biases, confounding factors, and downstream issues arising from data usage."],["Thoroughly understanding data characteristics and collection conditions is crucial for mitigating data pitfalls and ensuring robust machine learning models."],["Confirmation bias should be actively addressed, and data findings should be validated against intuition and common sense, prompting further investigation where discrepancies exist."],["Further insights into data analysis and interpretation can be gained from the listed additional reading materials covering topics like chart interpretation, statistical manipulation, and map-based data representation."]]],[]]
