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BSCS2007 - Machine Learning Techniques
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BSCS2007 - Machine Learning Techniques
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| Field | Value |
|---|---|
| Course Code | BSCS2007 |
| Level | Diploma Level Course |
| Credits | 4 |
| Type | Data Science |
| Pre-requisites | None |
| Videos | YouTube Playlist |
📖 Description
To introduce the main methods and models used in machine learning problems of regression, classification and clustering. To study the properties of these models and methods and learn about their suitability for different problems.
🗓️ Weekly Syllabus
| Week | Topic |
|---|---|
| Week 1 | Introduction; Unsupervised Learning - Representation learning - PCA |
| Week 2 | Unsupervised Learning - Representation learning - Kernel PCA |
| Week 3 | Unsupervised Learning - Clustering - K-means/Kernel K-means |
| Week 4 | Unsupervised Learning - Estimation - Recap of MLE + Bayesian estimation, Gaussian Mixture Model - EM algorithm. |
| Week 5 | Supervised Learning - Regression - Least Squares; Bayesian view |
| Week 6 | Supervised Learning - Regression - Ridge/LASSO |
| Week 7 | Supervised Learning - Classification - K-NN, Decision tree |
| Week 8 | Supervised Learning - Classification - Generative Models - Naive Bayes |
| Week 9 | Discriminative Models - Perceptron; Logistic Regression |
| Week 10 | Support Vector Machines |
| Week 11 | Ensemble methods - Bagging and Boosting (Adaboost) |
| Week 12 | Artificial Neural networks: Multiclass classification. |
📚 Books & Resources
Prescribed Books
The following are the suggested books for the course:
Pattern Classification by David G. Stork, Peter E. Hart, and Richard O. Duda Pattern Recognition and Machine Learning by Christopher M. Bishop The Elements of Statistical Learning: Data Mining, Inference, and Prediction by Trevor Hastie, Robert Tibshirani, and Jerome Friedman
📝 About the Instructors
Arun Rajkumar
Assistant Professor,
Department of Data Science and AI,
IIT Madras
I am currently an Assistant Professor at the Data Science and AI department of IIT Madras. Prior to joining IIT Madras, I was a research scientist at the Xerox Research Center (now Conduent Labs), Bangalore for three years. I earned my Ph.D from the Indian Institute of Science where I worked on 'Ranking from Pairwise Comparisons'. My research interests are in the areas of Machine learning, statistical learning theory with applications to education and healthcare.
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Other courses by the same instructor:
BSCS2004 -
Machine Learning Foundations
and
BSDA5007 -
Special topics in Machine Learning (Reinforcement Learning)