PyTorch
Overall Progress
0%
Tensors, requires_grad, backward, and autograd — with RL-relevant examples and explanations.
Reflect on your readiness across math, Python, NumPy, PyTorch, and RL concepts before starting the curriculum.
Bridge NumPy implementations to PyTorch. Build QNetwork and PolicyNetwork with nn.Module for RL.
Two-hidden-layer PyTorch network for Q-values; MSE loss.
PyTorch for RL: tensors, autograd, nn.Module, optimizers, and GPU.