Master Computer Vision OpenCV3 in Python and Machine Learning

.MP4, AVC, 200 kbps, 1280×720 | English, AAC, 128 kbps, 2 Ch | 6h 14m | 1.42 GB

Learn Computer Vision concepts by building 12 projects, including handwriting recognition, face filters, and car and people detection!

Computer vision applications and technology are exploding right now, with several apps and industries making amazing use of the technology”ranging from up-and-coming apps such as MSQRD, and PRISMA to billion-dollar apps such as Pokemon GO and Snapchat! Even Facebook, Google, Microsoft, Apple, Amazon, and Tesla are all heavily utilizing computer vision for face and object recognition, image searching, and especially in self-driving cars! As a result, the demand for computer vision expertise is growing exponentially! However, learning computer vision is hard! Existing online tutorials, textbooks, and free MOOCs are often outdated, using older and incompatible libraries, or are too theoretical, making the subject difficult to understand.

This was the author’s problem when learning Computer Vision and it became incredibly frustrating. Even simply running example code found online proved difficult as libraries and functions were often outdated. The author created this course to teach you all the key concepts without the heavy mathematical theory”all the while using the most up-to-date methods. At the end of the course, you will be able to build 12 awesome Computer Vision apps using OpenCV (the best supported open-source computer vision library that exists today!) in Python. Using it in Python is just fantastic as Python allows us to focus on the problem at hand without getting bogged down in complex code. If you’re an academic or college student but want to learn more, the author still points you in the right direction by linking the research papers for techniques used. So if you want to get an excellent foundation in Computer Vision, look no further. This is the course for you!

What You Will Learn

How to build complex Computer Vision applications using the latest techniques in OpenCV
Use Machine Learning and Augmented Reality in Computer Vision
Face detection and recognition (face swapping and filters!)
Object detection, tracking, and motion analysis
Handwriting recognition
Programming skills such as basic Python and NumPy
Understand how to use computer vision when executing cool startup ideas

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