Be part of the next generation of consumer and enterprise applications
What if you could learn and master some of the same techniques used in:
- Self-driving cars
- Microsoft Kinect
- Google image search
- Snapchat and Instagram filters
In this course, you will learn computer vision using Python. You’ll learn about image filtering and processing, pattern recognition, machine learning and face detection.
These technologies are powering the next generation of consumer and enterprise applications.
From the Internet of Things, to advertising and gaming. We want you to get on board and be part of this revolution.
The course includes theory, lots of live coding and examples, and
challenges for you to build your portfolio. Challenges include:
- Receipt Segmenter – Find text in an image
- Currency Counter – Count coins and dollar bills in an image
- Multi-object Matching – Find Legend of Zelda rupees using a patter matching algorithm
- Face Swap – App to swap the faces of two people
Complementing the application is the theory. We’ll discuss some of
the mathematics and processes that happen under the hood to give you a
better understanding of the concepts.
- Colorspace conversions
- Segmentation
- Filters
- Morphology
- Edge Detection
- Machine Learning
- Face detection
At the end of the course, students will learn the fundamental
computer vision techniques and be able to apply computer vision and
image processing to their own images for a variety of cool tasks like
building their own image filters, segmenting images, and even detecting
faces in images!
Course author
Mohit Deshpande is a software developer author of several ZENVA courses in iOS and Android development.
But first and foremost, Mohit is a computer scientist. His field of research and main areas of expertise are Computer Vision and Artificial Intelligence.
