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Introduction to Machine Learning [ELECTIVE]
30.2588

Description
ELECTIVE COURSE -> not offered every semester

Learning Objectives:
The students will be able to apply learning algorithms to building smart robots (perception, control), text understanding (web search, anti-spam), computer vision, medical informatics, audio, database mining, and other areas.

Content
1. Linear Regression with One Variable
2. Linear Algebra Review
3. Linear Regression with Multiple Variables
4. Logistic Regression
5. Regularization
6. Neural Networks: Representation
7. Neural Networks: Learning
8. Deep Learning
9. Decision trees
10. Machine Learning System Design
11. Unsupervised Learning (clustering)
12. Dimensionality Reduction
13. Anomaly Detection
14. Recommender Systems
15. Large Scale Machine Learning

ECTS credits
5

Teaching Language
English

Exam Language
English

Support Materials Language
English

Basic Learning Outcomes

Managing Entity (faculty)
Computer Science Department (HDA)