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(2) In future presentations of the research findings, in addition to the course project website and public presentations, your real name and personal information will not appear in this research report. If you are interested in the research results, we can provide you with an executive summary after the study is completed.
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Uedu Open / Introduction to Deep Learning
6.S191

Introduction to Deep Learning

Alexander Amini, Ava Soleimany | January IAP 2020
Data Science, Analytics & Computer Technology AI Software Design and Engineering Machine Learning Visualization Computer Science Engineering Artificial Intelligence
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CC BY-NC-SA 4.0
課程簡介
This is MIT’s introductory course on deep learning methods with applications to computer vision, natural language processing, biology, and more! Students will gain foundational knowledge of deep learning algorithms and get practical experience in building neural networks in TensorFlow. Course concludes with a project proposal competition with feedback from staff and panel of industry sponsors. Prerequisites assume calculus (i.e. taking derivatives) and linear algebra (i.e. matrix multiplication), and we’ll try to explain everything else along the way! Experience in Python is helpful but not necessary.
Course Information
SourceMIT 開放式課程
科系Electrical Engineering and Computer Science
LanguageEnglish
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