5. Alternative Methods for Getting Tensor Shape in PyTorch
   Understanding Tensors and Their Shapes:Tensors: In PyTorch, tensors are multi-dimensional arrays that serve as the fundamental data structure for deep learning
6. Extracting the Goodness: How to Access Values from PyTorch Tensors
   In PyTorch, a fundamental data structure is the tensor, which represents multi-dimensional arrays of numerical data. Tensors can hold various data types like floats
7. Taming Variable-Sized Data in PyTorch Dataloaders
   PyTorch Dataloader is a powerful utility for efficiently loading and managing datasets during training. However, it by default expects data samples to have consistent sizes across all dimensions
8. Building Neural Network Blocks: Effective Tensor Stacking with torch.stack
   In PyTorch, torch. stack is a function used to create a new tensor by stacking a sequence of input tensors along a specified dimension
9. Efficiently Converting 1-Dimensional PyTorch IntTensors to Python Integers
   Python: A general-purpose programming language widely used in data science and machine learning.PyTorch: A popular deep learning framework built on Python