Data Science
資料科學中最重要的四件事情是:
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資料準備和清理:資料科學的一個重要部分涉及收集、清理和準備資料。這包括識別缺失值、處理異常值以及將資料轉換為適合進行分析的格式等任務。
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探索性資料分析(EDA):EDA是分析和視覺化資料以了解其潛在模式和關係的過程。這一步驟對於識別資料中的趨勢和模式非常重要,進而幫助後續進行更深入的分析。
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機器學習演算法:機器學習演算法是資料科學中的核心,它們可用於從資料中學習並提取模式和洞察,以幫助做出更好的預測和決策。
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資料視覺化和傳達:資料視覺化是將資料轉換為易於理解和解釋的圖形和視覺化元素的過程。通過將資料呈現在圖表和圖形中,人們可以更容易地理解和傳達資料中的訊息和洞察。
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