DevanshKandpal: Bot: wrap bare course codes in wikilinks

2026-04-14T16:25:58Z

Bot: wrap bare course codes in wikilinks

← Older revision		Revision as of 16:25, 14 April 2026
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	\| credits = 4		\| credits = 4
	\| credit_structure = 3-0-2		\| credit_structure = 3-0-2
	\| pre_requisites = COL106, MTL106		\| pre_requisites = [[COL106]], [[MTL106]]
	\| overlaps = ELL409, ELL784		\| overlaps = [[ELL409]], [[ELL784]]
	}}		}}

	== COL341 : Fundamentals of Machine Learning ==		== COL341 : Fundamentals of Machine Learning ==
	Supervised Learning Algorithms: 1. Logistic Regression 2.Neural Networks 3.Decision Trees 4.Nearest Neighbour 5. Support Vector Machines 6. Naive Bayes. ML and MAP estimates. Bayes' Optimal Classifier. Introduction to Graphical Models. Generative Vs. Discriminative Models. Unsupervised learning algorithms: K-Means clustering, Expectation Maximization, Gaussian Mixture Models. PCA and Feature Selection, PAC Learnability, Reinforcement Learning. Some application areas of machine learning e.g. Natural Language Processing, Computer Vision, applications on the web. Introduction to advanced topics such as Statistical Relational Learning.		Supervised Learning Algorithms: 1. Logistic Regression 2.Neural Networks 3.Decision Trees 4.Nearest Neighbour 5. Support Vector Machines 6. Naive Bayes. ML and MAP estimates. Bayes' Optimal Classifier. Introduction to Graphical Models. Generative Vs. Discriminative Models. Unsupervised learning algorithms: K-Means clustering, Expectation Maximization, Gaussian Mixture Models. PCA and Feature Selection, PAC Learnability, Reinforcement Learning. Some application areas of machine learning e.g. Natural Language Processing, Computer Vision, applications on the web. Introduction to advanced topics such as Statistical Relational Learning.

Prashantt492: Creating course page via bot

2026-03-04T09:59:48Z

Creating course page via bot

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{{Infobox Course
| code = COL341
| name = Fundamentals of Machine Learning
| credits = 4
| credit_structure = 3-0-2
| pre_requisites = COL106, MTL106
| overlaps = ELL409, ELL784
}}

== COL341 : Fundamentals of Machine Learning ==
Supervised Learning Algorithms: 1. Logistic Regression 2.Neural Networks 3.Decision Trees 4.Nearest Neighbour 5. Support Vector Machines 6. Naive Bayes. ML and MAP estimates. Bayes' Optimal Classifier. Introduction to Graphical Models. Generative Vs. Discriminative Models. Unsupervised learning algorithms: K-Means clustering, Expectation Maximization, Gaussian Mixture Models. PCA and Feature Selection, PAC Learnability, Reinforcement Learning. Some application areas of machine learning e.g. Natural Language Processing, Computer Vision, applications on the web. Introduction to advanced topics such as Statistical Relational Learning.

COL341 - Revision history

DevanshKandpal: Bot: wrap bare course codes in wikilinks

Prashantt492: Creating course page via bot