https://machinelearning.subwiki.org/w/index.php?action=history&feed=atom&title=Unsupervised_learning
Unsupervised learning - Revision history
2026-07-30T00:34:33Z
Revision history for this page on the wiki
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https://machinelearning.subwiki.org/w/index.php?title=Unsupervised_learning&diff=3546&oldid=prev
Sebastian at 02:05, 12 May 2022
2022-05-12T02:05:23Z
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 02:05, 12 May 2022</td>
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<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>'''Unsupervised learning''' is a type of machine learning algorithm which does not supervise the model, but lets the model work on its own. The biggest difference between [[supervised learning]] and unsupervised learning is that the former deals with labeled data, while the latter deals with unlabeled data. While supervised learning is about function approximation, unsupervised learning is about description. Unsupervised learning has more difficult algorithms than [[supervised learning]]. Its goal is to automatically find structure in a dataset, to find the regularities in the input, to see what normally happens. Unsupervised learning assumes there is a structure to the input space which implies there are certain patterns that occur more often than others.</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>'''Unsupervised learning''' is a type of machine learning algorithm which does not supervise the model, but lets the model work on its own. The biggest difference between [[supervised learning]] and unsupervised learning is that the former deals with labeled data, while the latter deals with unlabeled data. While supervised learning is about function approximation, unsupervised learning is about description. Unsupervised learning has more difficult algorithms than [[supervised learning]]. Its goal is to automatically find structure in a dataset, to find the regularities in the input, to see what normally happens. Unsupervised learning assumes there is a structure to the input space which implies there are certain patterns that occur more often than others.</div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"></ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">While in supervised learning, the computer learns by making use of labeled data, in unsupervised learning, the computer learns by making use of unlabeled data.</ins></div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Accuracy is not a measure analized with unsupervised learning.</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Accuracy is not a measure analized with unsupervised learning.</div></td></tr>
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<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* [https://www.youtube.com/watch?v=yteYU_QpUxs Unsupervised Machine Learning Explained For Beginners. <code>youtube.com</code>]</ins></div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* [https://en.wikipedia.org/wiki/Unsupervised_learning Unsupervised learning. <code>wikipedia.org</code>]</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* [https://en.wikipedia.org/wiki/Unsupervised_learning Unsupervised learning. <code>wikipedia.org</code>]</div></td></tr>
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Sebastian
https://machinelearning.subwiki.org/w/index.php?title=Unsupervised_learning&diff=3545&oldid=prev
Sebastian: /* Resources */
2022-05-11T06:00:30Z
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 06:00, 11 May 2022</td>
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Sebastian
https://machinelearning.subwiki.org/w/index.php?title=Unsupervised_learning&diff=3544&oldid=prev
Sebastian: /* Resources */
2022-05-11T05:22:30Z
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 05:22, 11 May 2022</td>
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<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* [https://en.wikipedia.org/wiki/Unsupervised_learning Unsupervised learning. <code>wikipedia.org</code>]</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* [https://en.wikipedia.org/wiki/Unsupervised_learning Unsupervised learning. <code>wikipedia.org</code>]</div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* [https://www.ibm.com/cloud/learn/unsupervised-learning Unsupervised Learning. <code>ibm.com</code>]</ins></div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* [https://www.youtube.com/watch?v=jAA2g9ItoAc Lecture 1.3 — Unsupervised Learning — Machine Learning – Andrew Ng. <code>youtube.com</code>]</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* [https://www.youtube.com/watch?v=jAA2g9ItoAc Lecture 1.3 — Unsupervised Learning — Machine Learning – Andrew Ng. <code>youtube.com</code>]</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* [https://www.guru99.com/unsupervised-machine-learning.html#:~:text=Unsupervised%20Learning%20is%20a%20machine,deals%20with%20the%20unlabelled%20data. Unsupervised Machine Learning: Algorithms, Types with Example. <code>guru99.com</code>]</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* [https://www.guru99.com/unsupervised-machine-learning.html#:~:text=Unsupervised%20Learning%20is%20a%20machine,deals%20with%20the%20unlabelled%20data. Unsupervised Machine Learning: Algorithms, Types with Example. <code>guru99.com</code>]</div></td></tr>
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Sebastian
https://machinelearning.subwiki.org/w/index.php?title=Unsupervised_learning&diff=3543&oldid=prev
Sebastian at 05:19, 11 May 2022
2022-05-11T05:19:30Z
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Sebastian
https://machinelearning.subwiki.org/w/index.php?title=Unsupervised_learning&diff=3542&oldid=prev
Sebastian at 05:14, 11 May 2022
2022-05-11T05:14:03Z
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Sebastian
https://machinelearning.subwiki.org/w/index.php?title=Unsupervised_learning&diff=3539&oldid=prev
Sebastian at 04:41, 11 May 2022
2022-05-11T04:41:15Z
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<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Accuracy is not a measure analized with unsupervised learning.</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Accuracy is not a measure analized with unsupervised learning.</div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"></ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">Unsupervised learning is more representative of most real world problems.</ins></div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Applications ==</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Applications ==</div></td></tr>
</table>
Sebastian
https://machinelearning.subwiki.org/w/index.php?title=Unsupervised_learning&diff=3538&oldid=prev
Sebastian: /* Resources */
2022-05-11T04:37:13Z
<p><span dir="auto"><span class="autocomment">Resources</span></span></p>
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 04:37, 11 May 2022</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l39">Line 39:</td>
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<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* [https://www.youtube.com/watch?v=xtOg44r6dsE Supervised vs Unsupervised vs Reinforcement Learning. <code>youtube.com</code>]</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* [https://www.youtube.com/watch?v=xtOg44r6dsE Supervised vs Unsupervised vs Reinforcement Learning. <code>youtube.com</code>]</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* [https://www.youtube.com/watch?v=lEfrr0Yr684 Unsupervised Learning explained. <code>youtube.com</code>]</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* [https://www.youtube.com/watch?v=lEfrr0Yr684 Unsupervised Learning explained. <code>youtube.com</code>]</div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* [https://www.youtube.com/watch?v=-OEgiMH5aok Machine Learning Explained | Unsupervised Learning. <code>youtube.com</code>]</ins></div></td></tr>
</table>
Sebastian
https://machinelearning.subwiki.org/w/index.php?title=Unsupervised_learning&diff=3536&oldid=prev
Sebastian at 04:31, 11 May 2022
2022-05-11T04:31:03Z
<p></p>
<table style="background-color: #fff; color: #202122;" data-mw="interface">
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 04:31, 11 May 2022</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l1">Line 1:</td>
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<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>'''Unsupervised learning''' is a type of machine learning algorithm which does not supervise the model, but lets the model work on its own. The biggest difference between [[supervised learning]] and unsupervised learning is that the former deals with labeled data, while the latter deals with unlabeled data. While supervised learning is about function approximation, unsupervised learning is about description. Unsupervised learning has more difficult algorithms than [[supervised learning]]. Its goal is to automatically find structure in a dataset, to find the regularities in the input, to see what normally happens. Unsupervised learning assumes there is a structure to the input space which implies there are certain patterns that occur more often than others.</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>'''Unsupervised learning''' is a type of machine learning algorithm which does not supervise the model, but lets the model work on its own. The biggest difference between [[supervised learning]] and unsupervised learning is that the former deals with labeled data, while the latter deals with unlabeled data. While supervised learning is about function approximation, unsupervised learning is about description. Unsupervised learning has more difficult algorithms than [[supervised learning]]. Its goal is to automatically find structure in a dataset, to find the regularities in the input, to see what normally happens. Unsupervised learning assumes there is a structure to the input space which implies there are certain patterns that occur more often than others.</div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"></ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">Accuracy is not a measure analized with unsupervised learning.</ins></div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Applications ==</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Applications ==</div></td></tr>
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<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* [https://www.youtube.com/watch?v=D6gtZrsYi6c Unsupervised Learning | Unsupervised Learning Algorithms | Machine Learning Tutorial | Simplilearn. <code>youtube.com</code>]</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* [https://www.youtube.com/watch?v=D6gtZrsYi6c Unsupervised Learning | Unsupervised Learning Algorithms | Machine Learning Tutorial | Simplilearn. <code>youtube.com</code>]</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* [https://www.youtube.com/watch?v=xtOg44r6dsE Supervised vs Unsupervised vs Reinforcement Learning. <code>youtube.com</code>]</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* [https://www.youtube.com/watch?v=xtOg44r6dsE Supervised vs Unsupervised vs Reinforcement Learning. <code>youtube.com</code>]</div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* [https://www.youtube.com/watch?v=lEfrr0Yr684 Unsupervised Learning explained. <code>youtube.com</code>]</ins></div></td></tr>
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Sebastian
https://machinelearning.subwiki.org/w/index.php?title=Unsupervised_learning&diff=3535&oldid=prev
Sebastian: /* Applications */
2022-05-11T04:10:01Z
<p><span dir="auto"><span class="autocomment">Applications</span></span></p>
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 04:10, 11 May 2022</td>
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<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>The main applications of unsupervised learning are listed as follows.<ref>{{cite web |title=Real World Applications of Unsupervised Learning |url=https://pythonistaplanet.com/applications-of-unsupervised-learning/ |website=pythonistaplanet.com |accessdate=23 March 2020}}</ref></div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>The main applications of unsupervised learning are listed as follows.<ref>{{cite web |title=Real World Applications of Unsupervised Learning |url=https://pythonistaplanet.com/applications-of-unsupervised-learning/ |website=pythonistaplanet.com |accessdate=23 March 2020}}</ref></div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>* [[Clustering]]: The process of grouping the given data into different clusters or groups.</div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>* [[Clustering]]: The process of grouping the given data into different clusters or groups<ins style="font-weight: bold; text-decoration: none;">. Some examples of clustering include:</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">** Organizing computer clusters.</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">** Social network analysis.</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">** Market segmentation.</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">** Astronomical data analysis</ins>.</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* [[Visualization]]: The process of creating diagrams, images, graphs, charts, etc., to communicate some information.</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* [[Visualization]]: The process of creating diagrams, images, graphs, charts, etc., to communicate some information.</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* [[Dimensionality Reduction]]: The process of reducing the number of random variables under consideration by getting a set of principal variables.</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* [[Dimensionality Reduction]]: The process of reducing the number of random variables under consideration by getting a set of principal variables.</div></td></tr>
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Sebastian
https://machinelearning.subwiki.org/w/index.php?title=Unsupervised_learning&diff=3534&oldid=prev
Sebastian: /* Resources */
2022-05-11T04:03:52Z
<p><span dir="auto"><span class="autocomment">Resources</span></span></p>
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 04:03, 11 May 2022</td>
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<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* [https://en.wikipedia.org/wiki/Unsupervised_learning Unsupervised learning. <code>wikipedia.org</code>]</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* [https://en.wikipedia.org/wiki/Unsupervised_learning Unsupervised learning. <code>wikipedia.org</code>]</div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* [https://www.youtube.com/watch?v=jAA2g9ItoAc Lecture 1.3 — Unsupervised Learning — Machine Learning – Andrew Ng. <code>youtube.com</code>]</ins></div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* [https://www.guru99.com/unsupervised-machine-learning.html#:~:text=Unsupervised%20Learning%20is%20a%20machine,deals%20with%20the%20unlabelled%20data. Unsupervised Machine Learning: Algorithms, Types with Example. <code>guru99.com</code>]</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* [https://www.guru99.com/unsupervised-machine-learning.html#:~:text=Unsupervised%20Learning%20is%20a%20machine,deals%20with%20the%20unlabelled%20data. Unsupervised Machine Learning: Algorithms, Types with Example. <code>guru99.com</code>]</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* [https://www.youtube.com/watch?v=lEfrr0Yr684&t=27s Unsupervised Learning explained. <code>youtube.com</code>]</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* [https://www.youtube.com/watch?v=lEfrr0Yr684&t=27s Unsupervised Learning explained. <code>youtube.com</code>]</div></td></tr>
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Sebastian