fix many internal links
Fixed a number of internal links that need to go to the GitHub site. Ran `make www` to perform the above.
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@@ -228,11 +228,11 @@ The learning rate is hard-coded as `0.3`. No momentum factor is used.
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#### png corpora
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The [png-1](dlowe-aux-data/png-1) corpus was obtained by manually scraping the first results from an
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The `dlowe-aux-data/png-1` corpus was obtained by manually scraping the first results from an
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<https://images.google.com> search for "[obfuscate
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filetype:png](https://www.google.com/search?tbm=isch&sxsrf=APwXEddqIU34dxhpFdjEa8emNJKHOkYXIw:1683049158657&source=hp&biw=1727&bih=952&ei=xkpRZLapJtLKkPIP8bGKkAk&iflsig=AOEireoAAAAAZFFY1nbmEUHC74Cmg3Y5rEY1fV7ocASZ&ved=0ahUKEwi2pPXZltf-AhVSJUQIHfGYApIQ4dUDCAY&uact=5&oq=obfuscate+filetype:png&gs_lcp=CgNpbWcQA1AAWABg9QNoAHAAeACAATuIATuSAQExmAEAoAECoAEBqgELZ3dzLXdpei1pbWc&sclient=img&q=obfuscate&tbs=ift:png)".
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The [png-0](dlowe-aux-data/png-0) corpus was obtained by manually scraping the first results from an
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The `dlowe-aux-data/png-0` corpus was obtained by manually scraping the first results from an
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<https://images.google.com> search for "[obfuscate
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filetype:gif](https://www.google.com/search?tbm=isch&ved=2ahUKEwiowo7fltf-AhXSOUQIHbJBDp8Q2-cCegQIABAA&oq=obfuscate+filetype:gif&gs_lcp=CgNpbWcQAzoECCMQJzoHCAAQigUQQzoFCAAQgARQ6AxY6AxgpBJoAHAAeACAAUeIAcsBkgEBM5gBAKABAaoBC2d3cy13aXotaW1nwAEB&sclient=img&ei=0UpRZOiVINLzkPIPsoO5-Ak&bih=952&biw=1727&q=obfuscate&tbs=ift:gif)".
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@@ -242,7 +242,7 @@ filetype:gif](https://www.google.com/search?tbm=isch&ved=2ahUKEwiowo7fltf-AhXSOU
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* Using these corpora as a training set;
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* Using several hundred random `*.gif` and `*.png` files from my home computer as
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a test set;
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* Using the included [earlystop.pl](earlystop.pl) script, which stopped after 67000 iterations.
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* Using the included [earlystop.pl](%%REPO_URL%%/2011/dlowe/earlystop.pl) script, which stopped after 67000 iterations.
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* Interpreting output of `> 0.5` as "probably a `.png`" and `< 0.5` as "probably
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a `.gif`"
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@@ -303,7 +303,7 @@ representation and [endianness](https://en.wikipedia.org/wiki/Endianness).
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Making sure not to
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[overfit](https://en.wikipedia.org/wiki/Overfitting#Machine_learning) the network to the training data is a bit of a
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black art. I have enclosed [earlystop.pl](earlystop.pl), a wrapper script that implements
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black art. I have enclosed [earlystop.pl](%%REPO_URL%%/2011/dlowe/earlystop.pl), a wrapper script that implements
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a simple 'early stopping' algorithm; other techniques are possible.
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Bad input (e.g. nonexistent files, non-numeric number of iterations, etc.)
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@@ -501,10 +501,10 @@ assigned a target value of <code>0</code>. Intervening directories (if any) will
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intermediate target values.</p>
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<p>The learning rate is hard-coded as <code>0.3</code>. No momentum factor is used.</p>
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<h4 id="png-corpora">png corpora</h4>
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<p>The <a href="dlowe-aux-data/png-1">png-1</a> corpus was obtained by manually scraping the first results from an
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<p>The <code>dlowe-aux-data/png-1</code> corpus was obtained by manually scraping the first results from an
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<a href="https://images.google.com" class="uri">https://images.google.com</a> search for “<a href="https://www.google.com/search?tbm=isch&sxsrf=APwXEddqIU34dxhpFdjEa8emNJKHOkYXIw:1683049158657&source=hp&biw=1727&bih=952&ei=xkpRZLapJtLKkPIP8bGKkAk&iflsig=AOEireoAAAAAZFFY1nbmEUHC74Cmg3Y5rEY1fV7ocASZ&ved=0ahUKEwi2pPXZltf-AhVSJUQIHfGYApIQ4dUDCAY&uact=5&oq=obfuscate+filetype:png&gs_lcp=CgNpbWcQA1AAWABg9QNoAHAAeACAATuIATuSAQExmAEAoAECoAEBqgELZ3dzLXdpei1pbWc&sclient=img&q=obfuscate&tbs=ift:png">obfuscate
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filetype:png</a>”.</p>
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<p>The <a href="dlowe-aux-data/png-0">png-0</a> corpus was obtained by manually scraping the first results from an
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<p>The <code>dlowe-aux-data/png-0</code> corpus was obtained by manually scraping the first results from an
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<a href="https://images.google.com" class="uri">https://images.google.com</a> search for “<a href="https://www.google.com/search?tbm=isch&ved=2ahUKEwiowo7fltf-AhXSOUQIHbJBDp8Q2-cCegQIABAA&oq=obfuscate+filetype:gif&gs_lcp=CgNpbWcQAzoECCMQJzoHCAAQigUQQzoFCAAQgARQ6AxY6AxgpBJoAHAAeACAAUeIAcsBkgEBM5gBAKABAaoBC2d3cy13aXotaW1nwAEB&sclient=img&ei=0UpRZOiVINLzkPIPsoO5-Ak&bih=952&biw=1727&q=obfuscate&tbs=ift:gif">obfuscate
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filetype:gif</a>”.</p>
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<h5 id="results">Results:</h5>
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@@ -512,7 +512,7 @@ filetype:gif</a>”.</p>
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<li>Using these corpora as a training set;</li>
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<li>Using several hundred random <code>*.gif</code> and <code>*.png</code> files from my home computer as
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a test set;</li>
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<li>Using the included <a href="earlystop.pl">earlystop.pl</a> script, which stopped after 67000 iterations.</li>
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<li>Using the included <a href="https://github.com/ioccc-src/temp-test-ioccc/blob/master/2011/dlowe/earlystop.pl">earlystop.pl</a> script, which stopped after 67000 iterations.</li>
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<li>Interpreting output of <code>> 0.5</code> as “probably a <code>.png</code>” and <code>< 0.5</code> as “probably
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a <code>.gif</code>”</li>
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</ul>
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@@ -554,7 +554,7 @@ figuring out how to concatenate directory and file names…).</p>
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representation and <a href="https://en.wikipedia.org/wiki/Endianness">endianness</a>.</p>
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<p>Making sure not to
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<a href="https://en.wikipedia.org/wiki/Overfitting#Machine_learning">overfit</a> the network to the training data is a bit of a
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black art. I have enclosed <a href="earlystop.pl">earlystop.pl</a>, a wrapper script that implements
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black art. I have enclosed <a href="https://github.com/ioccc-src/temp-test-ioccc/blob/master/2011/dlowe/earlystop.pl">earlystop.pl</a>, a wrapper script that implements
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a simple ‘early stopping’ algorithm; other techniques are possible.</p>
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<p>Bad input (e.g. nonexistent files, non-numeric number of iterations, etc.)
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tends to result in empty output.</p>
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