Deep Learning - 097200
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Lecture |
Exercise |
Laboratory |
Project or
Seminar |
House
Work |
Weekly
Hours |
2 |
2 |
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3 |
3 |
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Determination of the grade according to progress during the semester and the submission of the final thesis
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Prerequisites:
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(
| | Data Structures 1 |
234218
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and
| Introduction to Machine Learning |
236756
| ) |
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or
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(
| | Data Structures and Algorithms |
094224
| |
| | |
and
| Machine Learning 1 |
096411
| ) |
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or
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(
| | Int. to Data Structur and Algorithms |
044268
| |
| | |
and
| Machine Learning |
046195
| ) |
| |
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Overlapping Courses:
| | | | Deep Learning and Its Applications |
236777
| |
The Course Covers Practical and Theoretical Aspects of Deep the Course Will Cover Shallow Networks, Deep Networks Convolutional Networks and Their Theoretical Analysis.
Learning Outcomes
At the End of the Course the Student Will Know:
1. to Execute Various Deep Learning Architectures.
2. to Analyze Their Generalization Properties
Created in 08/03/2021 Time 15:07:03
