Master Computer Vision™ OpenCV3 in Python and Machine Learning

This is the code repository for Master Computer Vision™ OpenCV3 in Python and Machine Learning, published by Packt. It contains all the supporting project files necessary to work through the video course from start to finish.

About the Video Course

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 Pokémon 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 Existing online tutorials, textbooks, and free MOOCs are often outdated, using older and incompatible libraries, or are too theoretical, making the subject difficult to understand.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 Even simply running example code found online proved difficult as libraries and functions were often outdated.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

Build a simple and powerful JavaScript scraping script.
Understand how to create a web scraping tool using JavaScript and Node JS.
Extract data from web pages with simple JavaScript programming and
libraries such as CasperJS, Cheerio, and express.js using a realistic example.
Find out how to automate these actions with JavaScript packages.
Learn to save the result to the cloud with S3 (AWS) using a NodeJS server.
Best Practices in Web Scraping.

Instructions and Navigation

Assumed Knowledge

To fully benefit from the coverage included in this course, you will need:
The course is for beginners who have an interest in computer vision and college students looking to get a head start before starting computer vision research. Anyone curious about using Deep Learning for Computer Vision; entrepreneurs looking to implement Computer Vision startup ideas; hobbyists wanting to make a cool Computer Vision prototype; and software developers and engineers wanting to develop a computer vision skillset will all benefit from this course.

Technical Requirements

This course has the following software requirements:

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