Machine Learning for Computer Vision
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.
What You'll Learn
Applies machine learning to computer vision tasks like image classification and object detection
Watch on External: Coursera ↗
(saves to browser)
Sign in to unlock AI tutor explanation · ⚡30
More on: CV Basics
View skill →Related AI Lessons
⚡
⚡
⚡
⚡
I Almost Quit Java After My First Project (Then One Bug Changed Everything)
Medium · Python
FastAPI for Production AI: From Notebook to Scalable APIs
Dev.to AI
Is BMAML correct decision, and how can one implement it?
Reddit r/deeplearning
Easiest Way to Understand Machine Learning Concepts
Medium · Machine Learning
🎓
Tutor Explanation
DeepCamp AI