STEM

Computer Vision for Data Scientists

Computer vision has come a long way since its humble beginnings. And today, it’s one of the most talked-about fields in tech. Join instructor Harpreet Sahota in this comprehensive overview of the history and evolution of this increasingly important industry, developing your understanding of convolutional neural networks, network training, deep learning models for image classification tasks, transfer learning with pretrained models, and more. Explore the wide variety of functionalities offered by the SuperGradients flexible training library, which gives you the power to shorten and streamline the model development lifecycle. Along the way, Harpreet shares practical insights on how to train models and networks more effectively, applying state-of-the-art techniques like exponential moving average, weighted average, batch accumulation, and BatchNorm.

Note: This course requires a basic working knowledge of machine learning as well as experience with Python and PyTorch.

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