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ENGINEERING FACULTY / COMPUTER ENGINEERING / BLM4030 - ADVANCED DEEP LEARNING
GENERAL INFORMATION ABOUT THE COURSE
Course Code
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Course Title
Theoretical
Practical
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Turkish Name of the Course
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Course Objective
History and theoretical advantages of deep learning, Basic neural network architectures and learning algorithms that can be used for deep learning, Organizing Distributed Models, Optimization Techniques for Training Deep Models, Convolutional networks, Feedback and recursive networks, Autoencoders and Linear Factor Models, Learning by Representation, Deep Generative Models - Boltzman Machines.
Brief Content of the Course
Deep learning methods, a sub-branch of machine learning, can perform high-level abstract modeling from labeled or unlabeled data. Recent advances in hardware and algorithms have made these methods widely used in big data analysis, computer vision and natural language processing. This course will explore the theoretical and practical aspects behind the popularity of deep learning methods. Practical experience will also be gained.
Prerequisites
None
Course Objectives
Course Objectives
Hedef Bulunamadı
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Course Category
Course Category
Percentage
Mathematics and Basic Sciences
Basic Vocational Courses
Expertise /Field Courses