(Music) Welcome to introduction to Computer Vision. In this course, you will get introduced to the field of computer vision, and we'll learn about its applications. Further, you will also learn about the specialized methods and techniques that make up the field of computer vision, and we'll learn to implement these techniques using Python. So let's get started. After completing this course, you will: understand what is computer vision, be able to apply and use computer vision algorithms with Python and OpenCV, know how to create your own custom classifiers that can be applied to business problems, build your own web app to classify images. What you will not learn, how computer vision works, how neural networks or deep learning work, math and statistics. To start, let's begin by understanding by what exactly is computer vision? What do you see in the following image? We can clearly see that this is a picture of a giraffe. As humans, when we see an image, we can instantaneously recognize the contents of the image and interpret it. Computers on the other hand, aren't capable of doing so. As you may have guessed, computer vision is about this. It is providing computers the ability to see and understand images. Now let's understand why computer vision is creating big waves in the industry. At a high level, the reason why computer vision or any technology is adopted, is because of some improvement. It could be that something slower becomes significantly faster, expensive becomes cheaper, manual becomes automated, difficult becomes easy, inconvenient becomes convenient, unscalable becomes scalable. One really groundbreaking change as we've seen in the news, is self-driving cars which frees up time for passengers through automation and can potentially save more lives than having human drivers. But in the course, we'd like to focus on smaller, more narrow solutions that use computer vision. Computer vision has applications in all industries and sectors. We have seen that computer vision has made an enormous impact especially in industries like automotive, manufacturing, human resources, insurance, healthcare, and many more. In fact, there isn't an industry where computer vision does not have an application. Now, let's dive right into how computer vision has been changing and disrupting industries. If you don't know much about the oil and gas industry and you're not familiar with what's happening in the United Arab Emirates then you probably won't know of this company called ADNOC, that produces about 3 million barrels of oil and 10.5 billion cubic feet of raw gas each day. Founded in 1971, the Abu Dhabi National Oil Company or ADNOC is a diversified group of energy and petrochemical companies. This Emirati firm has previously used a labor intensive process for classifying the characteristics of rock samples requiring precious time and energy from expert geologists. After geologists fed high resolution rock images into a database, they used IBM Watson to analyze and properly identify classes of carbonate rock, giving ADNOC the ability to classify up to 25,000 thin section rock images per day. With Watson, they can run a set of images for a whole reservoir in minutes, saving their expert geologists precious time. Let's look at another case of how computer vision is revolutionizing the hiring process. In the HR world, computer vision is changing how candidates get hired in the interview process. Knockri, a Canadian based startup, is making waves with their AI video soft skill assessment tool. By using computer vision, machine learning and data science, they're able to quantify soft skills and conduct early candidate assessments to help large companies shortlist the candidates. In this video, we saw how applications of computer vision are impacting our everyday lives. (Music)