finished chapter 2
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lem bei Klas-si-fi-zie-rungs-auf-ga-ben. Die Klas-
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st_5/conv_pool/upper_horiz_avgpooled.png> <../graphics/mnist_5/conv_pool/left_v
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\T1/LinuxBiolinumT-TLF/m/n/10 Quelle: https://towardsdatascience.com/common-los
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s-functions-in-machine-
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\T1/LinuxBiolinumT-TLF/m/n/10 https://www.bloomberg.com/news/articles/2019-12-1
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\T1/LinuxBiolinumT-TLF/m/n/10 https://www.technologyreview.com/f/614986/ai-face
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-recognition-racist-us-
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\T1/LinuxBiolinumT-TLF/m/n/10 https://github.com/vdumoulin/conv_arithmetic/blo
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Here is how much of TeX's memory you used:
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38572 strings out of 492609
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1388446 words of memory out of 5000000
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41751 multiletter control sequences out of 15000+600000
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1392484 words of memory out of 5000000
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41752 multiletter control sequences out of 15000+600000
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93620 words of font info for 122 fonts, out of 8000000 for 9000
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1143 hyphenation exceptions out of 8191
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Output written on Grundlagen_des_maschinellen_lernens.pdf (24 pages, 1424471 by
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Output written on Grundlagen_des_maschinellen_lernens.pdf (25 pages, 1428419 by
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tes).
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PDF statistics:
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543 PDF objects out of 1000 (max. 8388607)
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456 compressed objects within 5 object streams
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109 named destinations out of 1000 (max. 500000)
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551 PDF objects out of 1000 (max. 8388607)
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463 compressed objects within 5 object streams
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111 named destinations out of 1000 (max. 500000)
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440 words of extra memory for PDF output out of 10000 (max. 10000000)
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