Machine Learning for Computer Vision
Computer Vision for Engineering and Science,
In the second course of the Computer Vision for Engineering and Science specialization, you will perform two of the most common computer vision tasks: classifying images and detecting objects. You will apply the entire machine learning workflow, from preparing your data to evaluating your results. By the end of this course, you’ll train machine learning models to classify images of street signs and detect material defects. You will use MATLAB throughout this course. MATLAB is the go-to choice for millions of people working in engineering and science, and provides the capabilities you need to accomplish your computer vision tasks. You will be provided free access to MATLAB for the course duration to complete your work. To be successful in this specialization, it will help to have some prior image processing experience. If you are new to image data, it’s recommended to first complete the Image Processing for Engineering and Science specialization.
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| Rating | Not enough ratings |
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| Length | 5 weeks |
| Starts | Jul 3 (earlier today) |
| Cost | $49 |
| From | MathWorks via Coursera |
| Instructors | Matt Rich, Amanda Wang, Megan Thompson, Brandon Armstrong, Isaac Bruss |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Data Science Engineering Programming |
| Tags | Data Science Physical Science And Engineering Machine Learning Electrical Engineering |
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| Rating | Not enough ratings |
|---|---|
| Length | 5 weeks |
| Starts | Jul 3 (earlier today) |
| Cost | $49 |
| From | MathWorks via Coursera |
| Instructors | Matt Rich, Amanda Wang, Megan Thompson, Brandon Armstrong, Isaac Bruss |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Data Science Engineering Programming |
| Tags | Data Science Physical Science And Engineering Machine Learning Electrical Engineering |
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