8. Efficiently Locating True Elements in NumPy Matrices (Python)
   NumPy and ArraysNumPy (Numerical Python) is a powerful library in Python for working with arrays. Arrays are multidimensional collections of elements
9. Finding Dimensions and Size of NumPy Matrices in Python
   Here's how you can find the dimensions and size of a NumPy matrix:Using the shape attribute:The . shape attribute of a NumPy matrix returns a tuple that represents the number of elements in each dimension of the matrix
10. Beyond Reshaping: Alternative Methods for 1D to 2D Array Conversion in NumPy
    Understanding Arrays and MatricesConversion ProcessImport NumPy: Begin by importing the NumPy library using the following statement:import numpy as np
11. Beyond the Basics: Exploring Arrays and Matrices for Python Programmers
    NumPy Arrays vs. MatricesDimensionality:Arrays: Can be one-dimensional (vectors) or have many dimensions (multidimensional arrays). They are more versatile for storing and working with numerical data
12. Upgrading Your NumPy Workflow: Modern Methods for Matrix-to-Array Conversion
    NumPy Matrices vs. ArraysMatrices in NumPy are a subclass of arrays that represent two-dimensional mathematical matrices
13. Python Power Tools: Transposing Matrices with zip and List Comprehension
    Understanding zip function:zip accepts multiple iterables (like lists, tuples) and combines their elements into tuples.For lists of unequal length
14. Efficient Matrix Multiplication in PyTorch: Understanding Methods and Applications
    PyTorch and MatricesPyTorch is a popular Python library for deep learning. It excels at working with multi-dimensional arrays called tensors
15. Understanding Element-Wise Product of Vectors, Matrices, and Tensors in PyTorch
    ConceptIn linear algebra, the element-wise product multiplies corresponding elements at the same position in two tensors (vectors or matrices) of the same shape