Artificial Intelligence concepts are growing phenomenally in the recent past in all industries, especially in the field of data science. Traditionally, data scientists used to analyze the data, and apply complex statistical, math and computing tools in them to draw useful insights from the data. These insights would then help the concerned authorities to take the right, business-related decisions.
With the advent of technology and innovation, AI has been divided into many categories such as machine learning, deep learning and computer vision. The main objective of all the categories of AI is to make computers the human brain. Experts in AI write algorithms and use tools in such a way that computers can think just like the human brain. Computer vision is that subdivision of AI, where computers can visually comprehend and observe things, exactly the way the human brain sees and understands things. Keep reading to know more about computer vision and how it is used in data science.
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Modus operandi of computer vision models
We can see other things thanks to the signals that are sent from/to our optic nerves, retina and cortex. Computer vision, on the other hand, is a system that trains the systems to see and observe things at a much faster rate than humans. Loads and loads of images of a particular category are fed into the system to train it to recognize a particular image in that category.
For example, if you want to train a computer to recognize the image of a car, you have to feed thousands of vehicle images into the system to help it recognize a car from the lot, and then also differentiate between the different types of cars available.
How can you train the system to identify one particular image from the lot through algorithms? This is where you will need to use two important concepts of computer vision to take you forward – CNN (Convolutional Neural Network) and Deep Learning.
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Deep Learning – A branch of machine learning, deep learning is the concept where the machine or the computer learns by itself through the algorithms that are fed into it. The computer learns on its own to identify a particular image, and recognize it from thousands of other images shown. You don’t have to do any separate programming to train the computer in visual recognition, thanks to this concept.
CNN – Convolution, in mathematical terms, refers to an operation performed on two functions to give a third function as a result. So in the convolutional neural network concept, the data fed into the computer is broken down into images or pixels. Labels are assigned to these images or pixels, and the computer is trained to perform a convolution on these labels and predict the image correctly. Several convolutions are run until the desired accuracy is achieved.
Today, some of the most common computer vision applications include fraud detection, self-driving vehicles, X-ray analysis, traffic analysis and the like.
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Learning Computer Vision
Computer Vision is definitely a worthy course to learn, because the future of all industries is going to be AI-dominated. According to a recent study, the computer vision industry is expected to be worth a whopping $ 17.4 billion by the end of 2024, as all industries manufacturing a pin to a plane are expected to incorporate these fully-automated human technologies.
To learn the computer vision course, you must have strong knowledge of the concepts of Artificial Intelligence and Deep Learning. You should also know the fundamentals of math concepts (linear algebra and calculus), statistical concepts (probability distribution, hypothesis testing and regression analysis) and computing concepts (knowledge of programming languages, especially Python, and coding). However, if you don’t have a background in any of these, you don’t have to worry. You can find many free online courses giving you an overview of these concepts.
So, before you take up these highly-recommended computer vision training courses from data institutes in Bangalore, it is a good idea to go through the online resources about computer vision.
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Computer Vision Courses in Bangalore
First Principles of Computer Vision Specialization – Coursera in collaboration with Columbia University
Course details
- Career Certificate from Columbia University upon completion
- Course Duration – 7 months; 2 hours a week
- Topics covered – Camera & Imaging, Features & Boundaries, 3D Reconstruction with Single & multiple view points, Visual Perception and more
Introduction to Computer Vision and Image Processing – Coursera in collaboration with IBM
Course details
- Shareable career certificate from IBM upon completion of the course
- Designed for beginners in computer vision
- Course duration – 21 hours
- Topics covered – Introduction to Computer Vision, Image Processing with OpenCV and Pillow, Machine Learning Image Classification, Neural Networks & Deep Learning for Image Classification, Object Detection and Project Cases.
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Artificial Intelligence & Deep Learning Course – 360digiTMG
Course details
- Faculty members are alumni of some of the best institutes in India like IIM, IIT and ISB
- Job Placement Assistance Provided to students
- Completion Certificate from IBM
- Course Modules are covered through 80 hours of classroom & online sessions, 100 hours of practical assignments and 100 hours of hands-on experience on normal and two Capstone Live projects
- Course duration – 2.5months
- Course Fee- Rs.47200
- Topics Covered – Introduction to AI & Deep Learning, Introduction to Python Libraries, Machine Learning Primer, Mathematical Foundations, Deep Learning Primer, Perception Algorithm & Back Propagation Neural Network Algorithm, Artificial Neural Network, Image Processing & Computer Vision, CNN, RNN, Object Detection, Long Term Short Term Memory, Gates Recurrent Units, Functional APIs, Speech Recognition, Autoencoders, Auto and Explainable Artificial Intelligence and more
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We highly recommend the course from 360digiTMG for you to gain an in-depth understanding of the concepts used in computer vision and apply them in real-time cases. The best thing about this course is that it brushes up your knowledge of the fundamentals of Python and Math, which prepares you well for the advanced concepts that are covered in other modules. This is one of the most well-structured, flexible, versatile and career-providing courses on computer vision that you will ever come across when you look for such a course in Bangalore.
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