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Deep Learning Applications for Computer Vision に戻る

コロラド大学ボルダー校(University of Colorado Boulder) による Deep Learning Applications for Computer Vision の受講者のレビューおよびフィードバック



This course can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at In this course, you’ll be learning about Computer Vision as a field of study and research. First we’ll be exploring several Computer Vision tasks and suggested approaches, from the classic Computer Vision perspective. Then we’ll introduce Deep Learning methods and apply them to some of the same problems. We will analyze the results and discuss advantages and drawbacks of both types of methods. We'll use tutorials to let you explore hands-on some of the modern machine learning tools and software libraries. Examples of Computer Vision tasks where Deep Learning can be applied include: image classification, image classification with localization, object detection, object segmentation, facial recognition, and activity or pose estimation....



Deep Learning Applications for Computer Vision: 1 - 3 / 3 レビュー

by Erik S


P​rofessor Fleming is explaining verry good. Even is most of the concepts were not new to me it was a plessure how it was explained.

by Joed H P


G​reat introductory course on deep learning for computer vision.



good. Thanks