DEEP LEARNING (2 Credits)
Learning Outcomes: On successful completion of this course, student will be able to: Explain fundamental concepts of deep learning Execute a proper deep learning experimentation workflow A...
Learning Outcomes: On successful completion of this course, student will be able to: Explain fundamental concepts of deep learning Execute a proper deep learning experimentation workflow A...
Learning Outcomes: On successful completion of this course, students will be able to: LO1 - explain fundamental concepts of deep learning; LO2 - execute a proper deep learning experimentation workflo...
Learning Outcomes: On successful completion of this course, student will be able to: Explain the fundamental deep learning theory; Execute a proper deep learning experimentation workflow; Analyze a t...
Learning Outcomes: Topics:
Learning Outcomes: On successful completion of this course, student will be able to: LO1 - Explain the fundamental deep learning theory; LO2 - Execute proper deep learning experimentation workflows; ...
Learning Outcomes: On successful completion of this course, students will be able to: Identify various building blocks of deep learning; Comprehend the importance of deep learning in solving real lif...
Learning Outcomes: On successful completion of this course, students will be able to: LO1 - explain the fundamental deep learning theory; LO2 - execute a proper deep learning experimentation workflow...
Learning Outcomes: On successful completion of this course, students will be able to: LO1 - explain the fundamental deep learning theory; LO2 - execute a proper deep learning experimentation workflow...
Learning Outcomes: On successful completion of this course, students will be able to: define deep learning concepts and techniques; explain collection of data and preprocessing techniques for pre-pro...
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