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<div class="errata-body">
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<img style="float:left;width:150px;height:180px;border:1px solid black;margin:0px 10px 0px 0px;"
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src="./errata/Stevens-DLPy-HI.png">
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Errata: July 17, 2020
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<br/><br/>
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Thank you for purchasing
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<a href="https://www.manning.com/books/deep-learning-with-pytorch" target="_blank"><i>Deep
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Learning with PyTorch</i></a>.
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Please post errata not listed below in this book's <a
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href="https://livebook.manning.com/book/deep-learning-with-pytorch/welcome/v-13/" target="_blank">LiveBook
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Errata thread</a>.
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We'll update this list as necessary. Thank you!
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<br/><br/><br/><br/>
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<h2>Page xxviii</h2>
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<p>The "about this cover" section incorrectly identifies the individual on the cover as Kardinian, but he is
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Ka<strong>bard</strong>ian.</p>
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<h2>Page 5</h2>
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<p>Figure 1.1 was incorrectly flipped left-to-right.</p>
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<h2>Page 252</h2>
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<p><i>The final paragraph of section 9.4.4 should read:</i></p>
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<p>
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Once you have the candidates file and at least one subset downloaded, uncompressed,
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and put in the correct location, you should be able to start running the examples in
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the next chapter. If you want to jump ahead, you can use the p2ch10_explore_data.ipynb
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Jupyter Notebook to get started. Otherwise, we’ll return to the notebook in
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more depth in the next chapter. Hopefully your downloads will finish before you start
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needing to use the data!
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</p>
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<h2>Page 258</h2>
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<p><i>The first code annotation should read:</i></p>
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<p>
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Counts the number of lines
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that end with 1, which
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indicates it is a nodule
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</p>
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<p><i>The end of the first paragraph should read:</i></p>
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<p>
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(it’s a Boolean value: 0 for a candidate that is not a nodule, e.g. a blood vessel, and 1 for a
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candidate that is a nodule, which can be malignant or benign). We have 1,351 of the nodule candidates
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flagged as nodules.
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</p>
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</div>
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<div class="copyright">
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© 2018 Manning Publications Co. All rights reserved.
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</div>
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</body>
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</html>

errata/Stevens-DLPy-HI.png

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unicode-range: U+0100-024F, U+0259, U+1E00-1EFF, U+2020, U+20A0-20AB, U+20AD-20CF, U+2113, U+2C60-2C7F, U+A720-A7FF;
88+
}
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/* latin */
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@font-face {
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font-family: 'Lato';
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font-style: normal;
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font-weight: 400;
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src: local('Lato Regular'), local('Lato-Regular'), url(https://fonts.gstatic.com/s/lato/v16/S6uyw4BMUTPHjx4wXg.woff2) format('woff2');
95+
unicode-range: U+0000-00FF, U+0131, U+0152-0153, U+02BB-02BC, U+02C6, U+02DA, U+02DC, U+2000-206F, U+2074, U+20AC, U+2122, U+2191, U+2193, U+2212, U+2215, U+FEFF, U+FFFD;
96+
}
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/* latin-ext */
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@font-face {
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font-family: 'Lato';
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font-style: normal;
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font-weight: 700;
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src: local('Lato Bold'), local('Lato-Bold'), url(https://fonts.gstatic.com/s/lato/v16/S6u9w4BMUTPHh6UVSwaPGR_p.woff2) format('woff2');
103+
unicode-range: U+0100-024F, U+0259, U+1E00-1EFF, U+2020, U+20A0-20AB, U+20AD-20CF, U+2113, U+2C60-2C7F, U+A720-A7FF;
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}
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/* latin */
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@font-face {
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font-family: 'Lato';
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font-style: normal;
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font-weight: 700;
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src: local('Lato Bold'), local('Lato-Bold'), url(https://fonts.gstatic.com/s/lato/v16/S6u9w4BMUTPHh6UVSwiPGQ.woff2) format('woff2');
111+
unicode-range: U+0000-00FF, U+0131, U+0152-0153, U+02BB-02BC, U+02C6, U+02DA, U+02DC, U+2000-206F, U+2074, U+20AC, U+2122, U+2191, U+2193, U+2212, U+2215, U+FEFF, U+FFFD;
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}
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/* latin-ext */
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@font-face {
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font-family: 'Lato';
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font-style: normal;
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font-weight: 900;
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src: local('Lato Black'), local('Lato-Black'), url(https://fonts.gstatic.com/s/lato/v16/S6u9w4BMUTPHh50XSwaPGR_p.woff2) format('woff2');
119+
unicode-range: U+0100-024F, U+0259, U+1E00-1EFF, U+2020, U+20A0-20AB, U+20AD-20CF, U+2113, U+2C60-2C7F, U+A720-A7FF;
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}
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/* latin */
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@font-face {
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font-family: 'Lato';
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font-style: normal;
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font-weight: 900;
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src: local('Lato Black'), local('Lato-Black'), url(https://fonts.gstatic.com/s/lato/v16/S6u9w4BMUTPHh50XSwiPGQ.woff2) format('woff2');
127+
unicode-range: U+0000-00FF, U+0131, U+0152-0153, U+02BB-02BC, U+02C6, U+02DA, U+02DC, U+2000-206F, U+2074, U+20AC, U+2122, U+2191, U+2193, U+2212, U+2215, U+FEFF, U+FFFD;
128+
}

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