Computer Vision Masterclass For Free

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 Computer Vision Masterclass For Free

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What you’ll learn

  • Understand the basic intuition about Cascade and HOG classifiers to detect faces
  • Implement face detection using OpenCV and Dlib library
  • Learn how to detect other objects using OpenCV, such as cars, clocks, eyes, and full body of people
  • Compare the results of three face detectors: Haarcascade, HOG (Histogram of Oriented Gradients) and CNN (Convolutional Neural Networks)
  • Detect faces using images and the webcam
  • Understand the basic intuition about LBPH algorithm to recognize faces
  • Implement face recognition using OpenCV and Dlib library
  • Recognize faces using images and the webcam
  • Understand the basic intuition about KCF and CSRT algorithms to perform object tracking
  • Learn how to track objects in videos using OpenCV library
  • Learn everything you need to know about the theory behind neural networks, such as: perceptron, activation functions, weight update, backpropagation, gradient descent and a lot more
  • Implement dense neural networks to classify images
  • Learn how to extract pixels and features from images in order to build neural networks
  • Learn the theory behind convolutional neural networks and implement them using Python and TensorFlow
  • Implement transfer learning and fine tuning to get incredible results when classifying images
  • Use convolutional neural networks to classify the following emotions in images and videos: happy, anger, disgust, fear, surprise and neutral
  • Compress images using linear and convolutional autoencoders
  • Detect objects in images in videos using YOLO, one of the most powerful algorithms today
  • Recognize gestures and actions in videos using OpenCV
  • Learn how to create hallucinogenic images with Deep Dream
  • Learn how to revive famous artists with style transfer
  • Create images that don’t exist in the real world with GANs (Generative Adversarial Networks)
  • Implement image segmentation do extract useful information from images and videos

Requirements

  • Programming logic
  • Basic Python programming

Who this course is for:

  • Beginners who are starting to learn Computer Vision
  • Undergraduate students who are studying subjects related to Artificial Intelligence
  • People who want to solve their own problems using Computer Vision
  • Students who want to work in companies developing Computer Vision projects
  • People who want to know all areas inside Computer Vision, as well as know the problems that these techniques are able to solve
  • Anyone interested in Artificial Intelligence or Computer Vision
  • Data scientists who want to grow their portfolio
  • Professionals who want to understand how to apply Computer Vision to real projects
 

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