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Learn to implement a multi-class convolutional neural network (CNN) image classifier using PyTorch and the CIFAR-10 dataset. Follow along with this comprehensive 27-minute tutorial that covers data loading, model architecture design, training loop implementation, and model validation. Gain practical coding experience in Python and PyTorch while building a foundation for more advanced computer vision techniques. Explore topics such as CNN architecture, image classification, and model evaluation. Perfect for beginners looking to dive into deep learning and computer vision applications.
Syllabus
Intro:
Data loading recap:
Model architecture:
Training loop:
Testing our trained model on validation set:
Outro:
Taught by
rupert ai