Google 機器學習字典常見問題
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本文件會提出一些關於 Google 機器學習詞彙的引導式問題,並提供解答。
如何提出新詞彙?
按一下機器學習術語彙的頂端或底部「提供意見」按鈕。然後告訴我們缺少哪些字詞。
我可以檢舉不清楚的定義嗎?
沒錯!請按一下「提供意見」按鈕,向我們提供意見。
請透過電子郵件回覆我的意見回饋。
很抱歉,我們無法逐一回覆,但我們確實會審查所有意見回饋。
定義是由誰撰寫?
Google 團隊由技術撰稿人、研究人員和軟體工程師組成,他們會撰寫及審查每個定義。
您多久新增一次定義?
我們每年會三至四次發布新詞彙。此外,我們經常對現有定義進行小幅修改。
是否提供子詞彙表?
可以,您可以從頂端導覽列的「字典」下拉式選單中,選擇要篩選的字典主題。舉例來說,「Clustering」子詞彙集中於與叢集相關的詞彙。
目標對象是誰?
我們將「基礎」術語 (標有 🐣? 圖示) 的目標對象鎖定為機器學習新手。另一方面,我們也針對機器學習專家提供特定進階術語。
為什麼我的機構定義的術語與詞彙表不同?
在機器學習等相對較新的領域,這類問題相當常見。我們在此致上歉意,並保證機器學習術語可能永遠無法完全標準化。
為什麼有些定義看起來像是百科全書的條目?
有些詞彙只要單句定義就足夠,但其他詞彙則需要詳細的說明、圖片、比較、範例、數學公式等等。
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上次更新時間:2025-02-03 (世界標準時間)。
[null,null,["上次更新時間:2025-02-03 (世界標準時間)。"],[[["\u003cp\u003eThe Google Machine Learning Glossary allows users to propose new terms or report confusing definitions via the \u003cstrong\u003eSend Feedback\u003c/strong\u003e button.\u003c/p\u003e\n"],["\u003cp\u003eA team of Google technical writers, researchers, and software engineers are responsible for creating and maintaining the glossary's definitions.\u003c/p\u003e\n"],["\u003cp\u003eNew terms are added to the glossary in batches three to four times a year, and existing definitions are frequently updated.\u003c/p\u003e\n"],["\u003cp\u003eThe glossary can be filtered by topic using the \u003cstrong\u003eGlossary\u003c/strong\u003e drop-down, providing subglossaries focused on specific areas like clustering.\u003c/p\u003e\n"],["\u003cp\u003eThe glossary includes "Fundamentals" terms for newcomers, as well as advanced terms for experienced machine learning professionals.\u003c/p\u003e\n"]]],[],null,["# Frequently Asked Questions About Google's Machine Learning Glossary\n\nThis document asks and answers a few leading questions about\nGoogle's Machine Learning Glossary.\n\nHow do I propose a new term?\n----------------------------\n\nClick the **Send Feedback** button at the top or bottom of the Machine Learning\nGlossary. Then, tell us what term(s) are missing.\n\nCan I report a confusing definition?\n------------------------------------\n\nAbsolutely! Click the **Send Feedback** button and tell us.\n\nWill you email me a response to my feedback?\n--------------------------------------------\n\nUnfortunately not, but we really do review all feedback.\n\nWho writes the definitions?\n---------------------------\n\nA Google team of technical writers, researchers, and software engineers writes\nand reviews each definition.\n\nHow often do you add new definitions?\n-------------------------------------\n\nWe release batches of new terms three to four times per year. Additionally, we\nfrequently make minor changes to existing definitions.\n\nDo you provide subglossaries?\n-----------------------------\n\nYes, you can filter the glossary by choosing a topic from the **Glossary**\ndrop-down in the top navigation bar. For example, the **Clustering**\nsubglossary focuses on the terms relevant to, well, clustering.\n\nWho is the target audience?\n---------------------------\n\nWe aim the \"Fundamentals\" terms (those marked with a 🐣 icon) at\nmachine learning newcomers. At the other extreme, we aim certain advanced terms\nat experienced machine learning practitioners.\n\nWhy does my organization define terms differently than your glossary?\n---------------------------------------------------------------------\n\nThat's a pretty common problem in relatively new fields like machine learning.\nWe'll just offer our apologies and promise that machine learning terminology\nwill probably never be completely standardized.\n\nWhy do some definitions read like encyclopedia entries?\n-------------------------------------------------------\n\nA single sentence definition suffices for some terms, but other terms require\nextensive explanations, images, comparisons, examples, math formulas, and so on."]]