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Learn to build AI-controlled drones using computer vision, gesture control, and autonomous following capabilities with Raspberry Pi and Python.
Learn essential OpenCV Python techniques for image processing, including reading, displaying, and manipulating images, as well as drawing shapes and working with webcam video.
Learn essential microcontroller communication protocols like I2C, SPI, UART, Modbus RTU, CAN, USB, Ethernet, and PCIe in a fun and easy-to-understand format.
Learn to design custom Arduino PCBs using Altium Designer, from component creation to manufacturing-ready files. Gain practical skills for freelancing or PCB design careers.
Comprehensive introduction to machine learning algorithms, from regression to neural networks, with practical Python implementations and engaging whiteboard explanations for beginners and enthusiasts.
Learn to build 6 AR apps using ARCore and Unity, covering motion tracking, light estimation, hit testing, and advanced features like portals and multiplayer.
Learn to create interactive AR experiences using hand gestures. Build apps that respond to hand movements, from rotating 3D objects to shooting virtual blasts and smashing skulls in Unity.
Learn to implement YOLO v3 for robust object detection, from web scraping and dataset annotation to model training and deployment, using OpenCV and Python.
Learn to implement and train Mask R-CNN for instance segmentation using OpenCV and Python, covering installation, real-time applications, and custom object detection like potholes.
Learn to implement pose estimation using OpenPose, covering installation, people counting, fall detection, yoga pose recognition, and more. Gain practical skills in computer vision and deep learning applications.
Learn object detection and segmentation using Detectron2, covering installation, data preparation, and implementation with OpenCV and Python for computer vision applications.
Learn essential computer vision techniques using TensorFlow and MediaPipe. Build real-time applications for face detection, pose estimation, hand tracking, and object detection with Python and OpenCV.
Explore popular machine learning concepts through engaging lectures covering regression, clustering, neural networks, and more. Gain fundamental knowledge in an accessible, enjoyable format.
Learn advanced object detection techniques with YOLOR, covering implementation, optimization, and real-world applications in computer vision and AI. Gain practical skills for various industries.
Learn to implement YOLOX object detection, understand its speed and accuracy, explore non-max suppression, and build analytical dashboards using Plotly Dash for computer vision projects.
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