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	<id>https://wiki.devclub.in/index.php?action=history&amp;feed=atom&amp;title=ELL884</id>
	<title>ELL884 - Revision history</title>
	<link rel="self" type="application/atom+xml" href="https://wiki.devclub.in/index.php?action=history&amp;feed=atom&amp;title=ELL884"/>
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	<updated>2026-05-26T23:58:28Z</updated>
	<subtitle>Revision history for this page on the wiki</subtitle>
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	<entry>
		<id>https://wiki.devclub.in/index.php?title=ELL884&amp;diff=3146&amp;oldid=prev</id>
		<title>DevanshKandpal: Bot: wrap bare course codes in wikilinks</title>
		<link rel="alternate" type="text/html" href="https://wiki.devclub.in/index.php?title=ELL884&amp;diff=3146&amp;oldid=prev"/>
		<updated>2026-04-14T16:32:42Z</updated>

		<summary type="html">&lt;p&gt;Bot: wrap bare course codes in wikilinks&lt;/p&gt;
&lt;table style=&quot;background-color: #fff; color: #202122;&quot; data-mw=&quot;interface&quot;&gt;
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				&lt;td colspan=&quot;2&quot; style=&quot;background-color: #fff; color: #202122; text-align: center;&quot;&gt;← Older revision&lt;/td&gt;
				&lt;td colspan=&quot;2&quot; style=&quot;background-color: #fff; color: #202122; text-align: center;&quot;&gt;Revision as of 16:32, 14 April 2026&lt;/td&gt;
				&lt;/tr&gt;&lt;tr&gt;&lt;td colspan=&quot;2&quot; class=&quot;diff-lineno&quot; id=&quot;mw-diff-left-l4&quot;&gt;Line 4:&lt;/td&gt;
&lt;td colspan=&quot;2&quot; class=&quot;diff-lineno&quot;&gt;Line 4:&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class=&quot;diff-marker&quot;&gt;&lt;/td&gt;&lt;td style=&quot;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;&quot;&gt;&lt;div&gt;| credits = 3&lt;/div&gt;&lt;/td&gt;&lt;td class=&quot;diff-marker&quot;&gt;&lt;/td&gt;&lt;td style=&quot;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;&quot;&gt;&lt;div&gt;| credits = 3&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class=&quot;diff-marker&quot;&gt;&lt;/td&gt;&lt;td style=&quot;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;&quot;&gt;&lt;div&gt;| credit_structure = 3-0-0&lt;/div&gt;&lt;/td&gt;&lt;td class=&quot;diff-marker&quot;&gt;&lt;/td&gt;&lt;td style=&quot;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;&quot;&gt;&lt;div&gt;| credit_structure = 3-0-0&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class=&quot;diff-marker&quot; data-marker=&quot;−&quot;&gt;&lt;/td&gt;&lt;td style=&quot;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;&quot;&gt;&lt;div&gt;| pre_requisites = ELL409/ ELL784/ COL774&lt;/div&gt;&lt;/td&gt;&lt;td class=&quot;diff-marker&quot; data-marker=&quot;+&quot;&gt;&lt;/td&gt;&lt;td style=&quot;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;&quot;&gt;&lt;div&gt;| pre_requisites = &lt;ins style=&quot;font-weight: bold; text-decoration: none;&quot;&gt;[[&lt;/ins&gt;ELL409&lt;ins style=&quot;font-weight: bold; text-decoration: none;&quot;&gt;]]&lt;/ins&gt;/ &lt;ins style=&quot;font-weight: bold; text-decoration: none;&quot;&gt;[[&lt;/ins&gt;ELL784&lt;ins style=&quot;font-weight: bold; text-decoration: none;&quot;&gt;]]&lt;/ins&gt;/ &lt;ins style=&quot;font-weight: bold; text-decoration: none;&quot;&gt;[[&lt;/ins&gt;COL774&lt;ins style=&quot;font-weight: bold; text-decoration: none;&quot;&gt;]]&lt;/ins&gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class=&quot;diff-marker&quot; data-marker=&quot;−&quot;&gt;&lt;/td&gt;&lt;td style=&quot;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;&quot;&gt;&lt;div&gt;| overlaps = COL772&lt;/div&gt;&lt;/td&gt;&lt;td class=&quot;diff-marker&quot; data-marker=&quot;+&quot;&gt;&lt;/td&gt;&lt;td style=&quot;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;&quot;&gt;&lt;div&gt;| overlaps = &lt;ins style=&quot;font-weight: bold; text-decoration: none;&quot;&gt;[[&lt;/ins&gt;COL772&lt;ins style=&quot;font-weight: bold; text-decoration: none;&quot;&gt;]]&lt;/ins&gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class=&quot;diff-marker&quot;&gt;&lt;/td&gt;&lt;td style=&quot;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;&quot;&gt;&lt;div&gt;}}&lt;/div&gt;&lt;/td&gt;&lt;td class=&quot;diff-marker&quot;&gt;&lt;/td&gt;&lt;td style=&quot;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;&quot;&gt;&lt;div&gt;}}&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class=&quot;diff-marker&quot;&gt;&lt;/td&gt;&lt;td style=&quot;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;&quot;&gt;&lt;br&gt;&lt;/td&gt;&lt;td class=&quot;diff-marker&quot;&gt;&lt;/td&gt;&lt;td style=&quot;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;&quot;&gt;&lt;br&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class=&quot;diff-marker&quot;&gt;&lt;/td&gt;&lt;td style=&quot;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;&quot;&gt;&lt;div&gt;== ELL884 : Deep Learning for Natural Language processing ==&lt;/div&gt;&lt;/td&gt;&lt;td class=&quot;diff-marker&quot;&gt;&lt;/td&gt;&lt;td style=&quot;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;&quot;&gt;&lt;div&gt;== ELL884 : Deep Learning for Natural Language processing ==&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class=&quot;diff-marker&quot;&gt;&lt;/td&gt;&lt;td style=&quot;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;&quot;&gt;&lt;div&gt;Introduction to classical NLP, tokenization, N-gram language models and their evaluation, POS tagging (HMM, Viterbi, MEMM), Parsing (CKY parser), lexical and distributional semantics, introduction to deep learning (ANN, backpropagation, activation functions, RNNs, CNNs), RNN based language models, sequence-to-sequence models, attention and self-attention, transformer, advanced transformer architectures (BERT, RoBERTa, GPT), prompt-based learning, integrating knowledge in language models, retrieval-augmented models, editing neural networks, multilingual NLP, multimodal NLP, other applications of NLP, ethics in NLP, LLM and creativity. Courses of Study 2024-2025 Electrical Engineering 194&lt;/div&gt;&lt;/td&gt;&lt;td class=&quot;diff-marker&quot;&gt;&lt;/td&gt;&lt;td style=&quot;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;&quot;&gt;&lt;div&gt;Introduction to classical NLP, tokenization, N-gram language models and their evaluation, POS tagging (HMM, Viterbi, MEMM), Parsing (CKY parser), lexical and distributional semantics, introduction to deep learning (ANN, backpropagation, activation functions, RNNs, CNNs), RNN based language models, sequence-to-sequence models, attention and self-attention, transformer, advanced transformer architectures (BERT, RoBERTa, GPT), prompt-based learning, integrating knowledge in language models, retrieval-augmented models, editing neural networks, multilingual NLP, multimodal NLP, other applications of NLP, ethics in NLP, LLM and creativity. Courses of Study 2024-2025 Electrical Engineering 194&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;/table&gt;</summary>
		<author><name>DevanshKandpal</name></author>
	</entry>
	<entry>
		<id>https://wiki.devclub.in/index.php?title=ELL884&amp;diff=991&amp;oldid=prev</id>
		<title>Prashantt492: Creating course page via bot</title>
		<link rel="alternate" type="text/html" href="https://wiki.devclub.in/index.php?title=ELL884&amp;diff=991&amp;oldid=prev"/>
		<updated>2026-03-04T10:05:41Z</updated>

		<summary type="html">&lt;p&gt;Creating course page via bot&lt;/p&gt;
&lt;p&gt;&lt;b&gt;New page&lt;/b&gt;&lt;/p&gt;&lt;div&gt;{{Infobox Course&lt;br /&gt;
| code = ELL884&lt;br /&gt;
| name = Deep Learning for Natural Language processing&lt;br /&gt;
| credits = 3&lt;br /&gt;
| credit_structure = 3-0-0&lt;br /&gt;
| pre_requisites = ELL409/ ELL784/ COL774&lt;br /&gt;
| overlaps = COL772&lt;br /&gt;
}}&lt;br /&gt;
&lt;br /&gt;
== ELL884 : Deep Learning for Natural Language processing ==&lt;br /&gt;
Introduction to classical NLP, tokenization, N-gram language models and their evaluation, POS tagging (HMM, Viterbi, MEMM), Parsing (CKY parser), lexical and distributional semantics, introduction to deep learning (ANN, backpropagation, activation functions, RNNs, CNNs), RNN based language models, sequence-to-sequence models, attention and self-attention, transformer, advanced transformer architectures (BERT, RoBERTa, GPT), prompt-based learning, integrating knowledge in language models, retrieval-augmented models, editing neural networks, multilingual NLP, multimodal NLP, other applications of NLP, ethics in NLP, LLM and creativity. Courses of Study 2024-2025 Electrical Engineering 194&lt;/div&gt;</summary>
		<author><name>Prashantt492</name></author>
	</entry>
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