Titlebook: Machine Learning; The Basics Alexander Jung Textbook 2022 The Editor(s) (if applicable) and The Author(s), under exclusive license to Sprin

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書目名稱Machine Learning影響因子(影響力)




書目名稱Machine Learning影響因子(影響力)學(xué)科排名




書目名稱Machine Learning網(wǎng)絡(luò)公開度




書目名稱Machine Learning網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Machine Learning被引頻次




書目名稱Machine Learning被引頻次學(xué)科排名




書目名稱Machine Learning年度引用




書目名稱Machine Learning年度引用學(xué)科排名




書目名稱Machine Learning讀者反饋




書目名稱Machine Learning讀者反饋學(xué)科排名

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Alexander Jungegungen waren das . und das . Ist nun eine Raumkurve . gegeben, so kann man ebenso die m?glichen Bewegungen einer Geraden t betrachten, bei denen sie stets Tangente von . bleibt. Durch diese Bedingung allein ist indes eine solche Bewegung der Geraden im Raum noch nicht eindeutig bestimmt, weil sie s

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Alexander JungDas der geographischen Ortsbestimmung dienende Gradnetz der Erde geht dabei in das Gradnetz des Globus über, das einerseits aus den Gro?kreisen besteht, die durch zwei diametral gegenüberliegende Punkte, den . und den ., gehen und . hei?en, und anderseits aus den Parallelkreisen, die die Meridiane r

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Introduction, choose the right gear (clothing, wax) it is vital to have some idea for the maximum daytime temperature which is typically reached around early afternoon. If we expect a maximum daytime temperature of around plus 5 degrees, we might not put on the extra warm jacket but rather take only some extra s

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Model Validation and Selection,s . that incurs minimum average loss on some labeled data points that serve as the .. We refer to the average loss incurred by a hypothesis on the training set as the training error. The minimum average loss achieved by a hypothesis that solves the ERM might be referred to as the training error of t

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Feature Learning,urally from the available hard and software. For example, we might use the numeric measurement . delivered by a sensing device as a feature. However, we could augment this single feature with new features such as the powers . and . or adding a constant .. Each of these computations produces a new fe

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Transparent and Explainable ML,rent (or explainable) as explainable ML. Providing explanations for the predictions of a ML method is particulary important when these predictions inform decision making [.]. Explanations for automated decision making system have become a legal requirement [.].