978-3-95900-255-4

Marsoni

M251S

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978-3-95900-255-4Einsatz maschineller Lernverfahren zur lebenszyklusbasierten Energieprognose fr Werkzeugmaschinen Autor: Karl Doreth ISBN: 978 3 95900 255 4 Dissertation, Leibniz Universitt Hannover, 2019 Herausgeber der Reihe: Berend Denkena Band Nr.: IFW 4 2019 Umfang: 143 Seiten, 74 Abbildungen Schlagworte: Energieeffizienz, Werkzeugmaschinen, Support Vector Machine, maschinelles Lernen Kurzfassung: Steigende Energiekosten machen den Energieverbrauch von

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Similar criticism to my review of the Black Holes book: "Starts off ok, but quickly loses you. I have an extensive science education and quickly got lost. This topic cannot be easily explained in a brief book - the author is forced to jump over certain building blocks, and that just leaves the reader confused. I think this book series is good, but maybe not for abstract science topics."

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Reviewed in the United States on February 11, 2026

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Rusty.

San Leandro, US

★★★★★ 5

A fun read. Learned a lot.

Format: Kindle

I never expected to be able to understand Relativity or the more ethereal concepts of time. But Jenann brought them to my level. The language gets a bit flowery at times but I think that reflects that these ideas have a poetry of their own. RL

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Reviewed in the United States on July 10, 2023

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Kindle Customer

San Leandro, US

★★★★★ 5

Clear, Concise, and Compelling

Format: Kindle

The author takes us in an extraordinary trip through and about time. In particular, the discussion about Einstein’s Special and General Theories of Relativity were illuminating, clarifying a complex aspect of the nature of the universe. How should we think about time? This book will help the reader arrive at answers to that question.

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Reviewed in the United States on November 30, 2021

Los Angeles, US

★★★★★ 5

Deep important and illuminating

Format: Kindle

Worth a second read. I keep going back to it.

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Reviewed in the United States on July 2, 2023