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 https://www.coursera.org/degrees/master-of-science-data-science-boulder.
Deep Learning Applications for Computer Vision
コロラド大学ボルダー校（University of Colorado Boulder）このコースについて
12,527 最近の表示
柔軟性のある期限
スケジュールに従って期限をリセットします。
共有できる証明書
修了時に証明書を取得
100%オンライン
自分のスケジュールですぐに学習を始めてください。
中級レベル
Basic calculus (differentiation and integration), linear algebra
約22時間で修了
英語
字幕：英語
学習内容
Learners will be able to explain what Computer Vision is and give examples of Computer Vision tasks.
Learners will be able to describe the process behind classic algorithmic solutions to Computer Vision tasks and explain their pros and cons.
Learners will be able to use hands-on modern machine learning tools and python libraries.
習得するスキル
- Computer Vision
- Convolutional Neural Network
- Machine Learning
- Deep Learning
柔軟性のある期限
スケジュールに従って期限をリセットします。
共有できる証明書
修了時に証明書を取得
100%オンライン
自分のスケジュールですぐに学習を始めてください。
中級レベル
Basic calculus (differentiation and integration), linear algebra
約22時間で修了
英語
字幕：英語
提供：
コロラド大学ボルダー校（University of Colorado Boulder）
CU-Boulder is a dynamic community of scholars and learners on one of the most spectacular college campuses in the country. As one of 34 U.S. public institutions in the prestigious Association of American Universities (AAU), we have a proud tradition of academic excellence, with five Nobel laureates and more than 50 members of prestigious academic academies.
修士号の取得を目指しましょう
この コース は コロラド大学ボルダー校（University of Colorado Boulder） の100%オンラインの Master of Science in Data Science の一部です。
プログラムのすべてで認定されれば、それらのコースが学位学習に加算されます。
シラバス - 本コースの学習内容
4時間で修了
Introduction and Background
In this module, you will learn about the field of Computer Vision. Computer Vision has the goal of extracting information from images. We will go over the major categories of tasks of Computer Vision and we will give examples of applications from each category. With the adoption of Machine Learning and Deep Learning techniques, we will look at how this has impacted the field of Computer Vision.
4時間で修了
4件のビデオ （合計80分）, 10 学習用教材, 1 個のテスト
4時間で修了
Classic Computer Vision Tools
In this module, you will learn about classic Computer Vision tools and techniques. We will explore the convolution operation, linear filters, and algorithms for detecting image features.
4時間で修了
5件のビデオ （合計115分）, 10 学習用教材, 1 個のテスト
3時間で修了
Image Classification in Computer Vision
In this module we will first review the challenges for object recognition in Classic Computer Vision. Then we will go through the steps of achieving object recognition and image classification in the Classic Computer Vision pipeline.
3時間で修了
3件のビデオ （合計45分）, 2 学習用教材, 1 個のテスト
5時間で修了
Neural Networks and Deep Learning
In this module we will compare how the image classification pipeline with neural networks differs than the one with classic computer vision tools. Then we will review the basic components of a neural network. We will conclude with a tutorial in Tensor flow where we will practice how to build, train and use a neural network for image classification predictions.
5時間で修了
4件のビデオ （合計100分）, 5 学習用教材, 1 個のテスト
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