Deep Learning
Deep Learning
intermediate
Deep Learning with PyTorch: Fundamentals to Fine-Tuning
Autograd from first principles, then real training loops: learning-rate schedules, mixed precision, gradient accumulation, distributed data parallel, and the debugging discipline for a loss that will not go down. Finishes by fine-tuning a pretrained model on a custom dataset with a proper evaluation harness.
HT
Hiroshi Tanaka
4.9
$99.00
22 hours