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Explore variational autoencoders, generative models, and stochastic optimization in this concise lecture by Paul Hand from Northeastern University.
Explore gradient descent in deep neural networks with Paul Hand's lecture from Northeastern University. Learn about learning rates and convergence for convex functions in under an hour.
Explore continual learning and catastrophic forgetting in deep neural networks with Paul Hand from Northeastern University. Learn about regularization, dynamic architectures, and Complementary Learning Systems in under 1 hour.
Explore adversarial examples for deep neural networks in this short lecture by Paul Hand from Northeastern University. Learn about white and black box attacks, real-world attacks, and adversarial training.
Explore neural network architectures for image processing in this concise lecture by Paul Hand from Northeastern University. Learn about classification, segmentation, denoising, and more in under an hour.
Dive into supervised machine learning with Paul Hand's lecture from Northeastern University. Understand deep neural networks, loss functions, and the bias-variance tradeoff in under an hour.
Dive into Deep Image Prior, Deep Decoder, and Deep Geometric Prior for inverse imaging problems in this less than 1-hour online lecture by Paul Hand from Northeastern University.
Dive into the theory of GAN priors in Compressed Sensing with this less than 1-hour online lecture by Paul Hand from Northeastern University.
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