3. Beyond -1: Exploring Alternative Methods for Reshaping NumPy Arrays
   Reshaping Arrays in NumPyNumPy arrays are powerful data structures for numerical computations. Their shape determines how the elements are arranged in memory
4. Reshaping Tensors in PyTorch: Mastering Data Dimensions for Deep Learning
   Reshaping Tensors in PyTorchIn PyTorch, tensors are multi-dimensional arrays that hold numerical data. Reshaping a tensor involves changing its dimensions (size and arrangement of elements) while preserving the total number of elements
5. Understanding Tensor Reshaping with PyTorch: When to Use -1 and Alternatives
   In PyTorch, the view function is used to reshape a tensor without copying its underlying data. It allows you to modify the tensor's dimensions while maintaining the same elements