Professional Certificate in PyTorch Applications for Computer Vision
-- ViewingNowThe Professional Certificate in PyTorch Applications for Computer Vision is a crucial course designed to equip learners with the essential skills needed to thrive in the AI industry. This program focuses on PyTorch, a popular open-source machine learning library, and its applications in computer vision, a field that deals with how computers can gain high-level understanding from digital images or videos.
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⢠Unit 1: Introduction to PyTorch – Understanding the basics of PyTorch, its architecture, and how it compares to other popular deep learning libraries.
⢠Unit 2: Computer Vision Basics – Learning the fundamentals of computer vision, including image processing techniques and image classification.
⢠Unit 3: PyTorch for Computer Vision – Exploring how PyTorch can be used for computer vision applications.
⢠Unit 4: Convolutional Neural Networks (CNNs) – Delving into the specifics of CNNs, including network architecture, training, and optimization techniques.
⢠Unit 5: Object Detection – Understanding object detection techniques, such as Single Shot MultiBox Detector (SSD) and You Only Look Once (YOLO), and how to implement them using PyTorch.
⢠Unit 6: Semantic Segmentation – Learning about semantic segmentation, including the use of fully convolutional networks (FCNs) and U-Net, and how to implement them using PyTorch.
⢠Unit 7: Transfer Learning – Exploring transfer learning techniques and how to use pre-trained models in PyTorch.
⢠Unit 8: Generative Adversarial Networks (GANs) – Understanding the principles of GANs and how to implement them using PyTorch.
⢠Unit 9: Real-World Applications – Applying PyTorch and computer vision techniques to real-world applications, such as facial recognition, autonomous vehicles, and medical imaging.
⢠Unit 10: Best Practices – Learning best practices for developing and deploying PyTorch applications for computer vision.
Note: The above list of units is not exhaustive and may vary based on the specific needs and goals
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