Object-Oriented Programming and PyTorch Basics

Define and instantiate a simple Python class with attributes and methods.

Explain the concept of inheritance by creating a child class.

Create and manipulate tensors in PyTorch, including changing their device (CPU/GPU).

Perform mathematical operations on PyTorch tensors.

Use PyTorch's autograd feature to compute gradients automatically.

Explain the structure of an artificial neuron and the role of weights and biases.

Describe common activation functions (ReLU, Sigmoid, Softmax) and their use cases.

Build a simple neural network model by creating a class that inherits from torch.nn.Module.