Computer Vision
Enable machines to see and interpret the visual world. Learn about image classification, object detection, and segmentation using deep learning.
73 courses
Master image processing, object detection, and deep learning models using Python and OpenCV to build intelligent visual applications from scratch.
Master CNNs using Python and TensorFlow to build powerful image classification and text analysis models for real-world data science applications.
Build practical models for object detection, neural style transfer, and image generation using Python, Keras, and TensorFlow.
Learn to build intelligent systems that can recognize faces, detect objects, and analyze visual data using modern Python libraries and deep learning techniques.
Build and train your first Convolutional Neural Network from scratch in Python to classify images using the classic CIFAR-10 dataset.
Master object detection and image classification by applying transfer learning and modern neural network architectures using Python and TensorFlow.
Build a solid foundation in computer vision by learning to manipulate images, process real-time video, and detect objects using OpenCV and Python.
Build real-world image processing and object detection applications using OpenCV, TensorFlow, and Python.
Learn to process images and videos while implementing face and motion detection logic through clear, written explanations and practical Python exercises.
Master the fundamentals of image recognition and object detection by implementing CNNs, YOLO, and GANs using modern Python frameworks.
Build and deploy a deep learning classifier to detect face masks in real-time images and video streams using TensorFlow, Keras, and OpenCV.
Build and deploy image classification, object detection, and segmentation models from scratch using modern deep learning frameworks.
Learn to detect faces and identify age, gender, and emotions using modern deep learning models and Python libraries.
Build a foundation in image recognition and text extraction by mastering OpenCV and Tesseract through practical written guides.
Learn the fundamentals of computer vision by writing Python scripts to process, manipulate, and analyze images using the powerful OpenCV library.
Learn to train, evaluate, and deploy custom YOLO models for object detection, instance segmentation, and pose estimation using modern computer vision pipelines.
Master the basics of image processing and neural networks to build your own intelligent computer vision applications on the Raspberry Pi.
Build automated text recognition systems for images and video using Tesseract, EasyOCR, and custom neural networks.
Learn to build a deep learning computer vision pipeline, extract text with OCR, and deploy your model as a functional web application using Python.
Master the essentials of image processing and deep learning to build real-time object detection and change monitoring applications using Python, OpenCV, and TensorFlow.
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