Deep Learning on Cloud Platforms. (3-0) 3 Credit Hours

Catalog description

This course presents students with basic understanding of modern neural networks and their applications in computer vision and natural language processing (NLP). The course starts with a recap of linear models and discussion of stochastic optimization methods that are crucial for training deep neural networks. students will examine all of the popular neural network building blocks including fully connected layers, convolution, and recurrent layers. In this course, students will gain a thorough introduction to cutting-edge topics such as attention and transformer in Deep Learning for NLP using public cloud platforms. Students will also gain practical hands-on experience in the optimization, deployment, and scaling ML models of various types. The prerequisites for this course are: 1) Basic knowledge of Python. 2) Basic linear algebra and probability. This course has Differential Tuition. Course Fees: ISCS $75.