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Book: Maschinelles Lernen: Die Grundlagen

27/04/2024
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Price: 58,31 €
(as of Nov 02, 2024 11:29:08 UTC – Details)

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«Machine learning (ML) has become an everyday element in our lives and a standard tool for many areas of science and technology. To get the most out of ML, it is important to understand the underlying principles.”

In this book, ML is considered as the computational implementation of scientific principle. This principle involves continually adjusting a model of a given data-generating phenomenon by minimizing a form of loss that arises from its predictions.

The book empowers the reader to break down different ML applications and methods into three components (data, model, and loss), thereby helping them select from the wide range of ready-made ML methods.

The book's three-component approach allows for a consistent and transparent representation of various ML techniques. Important methods for regularization, privacy protection, and explainability of ML methods are special cases of this three-component approach.

 

Publisher ‏ : ‎ Springer-Verlag GmbH; 1. Aufl. 2024 edition (February 14, 2024)
Language ‏ : ‎ German
Hardcover ‏ : ‎ 252 pages
ISBN-10 ‏ : ‎ 9819979714
ISBN-13 ‏ : ‎ 978-9819979714
Product weight ‏ : ‎ 593 g
Dimensions: 16 x 1.9 x 24.1 cm

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Comments (15)

Does anyone else think that Book: Maschinelles Lernen: Die Grundlagen could have gone into more depth on the topic of supervised learning algorithms? I think it is a critical aspect in machine learning and deserved more attention. What do you think?

I don't understand why the author focuses so much on the technical aspects of the book Maschinelles Lernen: Die Grundlagen. Wouldn't it be more interesting to discuss the social and ethical implications of machine learning? Also, why don't you mention anything about the accessibility of this book to non-experts on the subject?

Perhaps because it is a technical book, not a social or ethical reflection. Regarding accessibility, it is subjective.

I just read the article about Book: Maschinelles Lernen: Die Grundlagen. Does anyone else think they could have gone deeper into supervised learning algorithms? It seemed to me that they fell short in that regard. Also, don't you think that artificial intelligence and machine learning are two sides of the same coin? Come on, I would like to read your opinions!

Totally agree with the approach of the article on Book: Maschinelles Lernen: Die Grundlagen. But don't you think we should discuss more about the ethical implications of machine learning? It's great to talk about technical advances, but ethics shouldn't take a backseat.

I agree, ethics in AI is crucial, not just its technical advances. Good point.

I find it interesting that the article mentions Book: Maschinelles Lernen: Die Grundlagen, but how does this compare to other books on machine learning? Are there any others that are more accessible for beginners? Also, is this book suitable for those who have no programming experience?

Try Machine Learning for Dummies. More accessible and you don't need to know how to program.

Interesting article about the Book: Maschinelles Lernen: Die Grundlagen. Don't you think that too much emphasis is being placed on the technical part and the human side of machine learning is being forgotten? Ethics and regulation are just as important, perhaps more so. What do you think, colleagues?

Has anyone noticed that the book Maschinelles Lernen: Die Grundlagen focuses too much on theory and less on practical aspects? Wouldn't it be more useful if it incorporated more real-life examples and practical applications of machine learning? Anyway, it's always good to have different perspectives.

Sometimes theory is necessary to understand practice well. Diversity of approaches is key.

I was wondering if anyone else noticed that the article mentioned little about supervised learning algorithms in Book: Maschinelles Lernen: Die Grundlagen. It seems to me to be a crucial topic in machine learning. Don't you think it should have had more depth in that aspect?

Totally agree, the book overlooked such a fundamental aspect.

Interesting article about the Book: Maschinelles Lernen: Die Grundlagen. But don't you think there's a little more depth missing in the practical application of machine learning? It seems to me that they focus too much on theory and forget the importance of actual implementation.

Totally agree. Theory is useful, but without practice, what value is it really?