COL774: Difference between revisions
| [checked revision] | [checked revision] |
Prashantt492 (talk | contribs) Creating course page via bot |
Bot: wrap bare course codes in wikilinks |
||
| Line 4: | Line 4: | ||
| credits = 4 | | credits = 4 | ||
| credit_structure = 3-0-2 | | credit_structure = 3-0-2 | ||
| pre_requisites = MTL106 OR Equivalent | | pre_requisites = [[MTL106]] OR Equivalent | ||
| overlaps = COL341 ELL784, ELL888 | | overlaps = [[COL341]] [[ELL784]], [[ELL888]] | ||
}} | }} | ||
== COL774 : Machine Learning == | == COL774 : Machine Learning == | ||
Supervised learning algorithms: Linear and Logistic Regression, Gradient Descent, Support Vector Machines, Kernels, Artificial Neural Networks, Decision Trees, ML and MAP Estimates, K-Nearest Neighbor, Naive Bayes, Introduction to Bayesian Networks. Unsupervised learning algorithms: K-Means clustering, Gaussian Mixture Models, Learning with Partially Observable Data (EM). Dimensionality Reduction and Principal Component Analysis. Bias Variance Trade- off. Model Selection and Feature Selection. Regularization. Learning Theory. Introduction to Markov Decision Processes. Application to Information Retrieval, NLP, Biology and Computer Vision. Advanced Topics. | Supervised learning algorithms: Linear and Logistic Regression, Gradient Descent, Support Vector Machines, Kernels, Artificial Neural Networks, Decision Trees, ML and MAP Estimates, K-Nearest Neighbor, Naive Bayes, Introduction to Bayesian Networks. Unsupervised learning algorithms: K-Means clustering, Gaussian Mixture Models, Learning with Partially Observable Data (EM). Dimensionality Reduction and Principal Component Analysis. Bias Variance Trade- off. Model Selection and Feature Selection. Regularization. Learning Theory. Introduction to Markov Decision Processes. Application to Information Retrieval, NLP, Biology and Computer Vision. Advanced Topics. | ||
Latest revision as of 16:26, 14 April 2026
| COL774 | |
|---|---|
| Machine Learning | |
| Credits | 4 |
| Structure | 3-0-2 |
| Pre-requisites | MTL106 OR Equivalent |
| Overlaps | COL341 ELL784, ELL888 |
COL774 : Machine Learning
Supervised learning algorithms: Linear and Logistic Regression, Gradient Descent, Support Vector Machines, Kernels, Artificial Neural Networks, Decision Trees, ML and MAP Estimates, K-Nearest Neighbor, Naive Bayes, Introduction to Bayesian Networks. Unsupervised learning algorithms: K-Means clustering, Gaussian Mixture Models, Learning with Partially Observable Data (EM). Dimensionality Reduction and Principal Component Analysis. Bias Variance Trade- off. Model Selection and Feature Selection. Regularization. Learning Theory. Introduction to Markov Decision Processes. Application to Information Retrieval, NLP, Biology and Computer Vision. Advanced Topics.