NumPy Broadcasting Functionality and Computation On Arrays In Python Data Science

In this NumPy Python Data Science Tutorial, We Discuss NumPy Broadcasting functionality. This NumPy Data Science Essential Training Series Covers Basics Concepts related to Numpy, Python and Data science.
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** What is NumPy Broadcasting?

*** The word broadcasting describes how numpy treats arrays with diverse shapes during arithmetic operations. Subject to certain constraints, the smaller array is “broadcast” across the larger array so that they have compatible shapes. Broadcasting provides a means of vectorizing array operations so that looping occurs in C instead of Python. It does this without making needless copies of data and usually leads to effective algorithm implementations. There are, however, cases where broadcasting is a bad idea because it leads to inefficient use of memory that slows computation.
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** What is NumPy ?

*** NumPy is the ultimate package for scientific computing with Python. It contains among other things: a powerful N-dimensional array object, tools for integrating C/C++ and Fortran code, sophisticated (broadcasting) functions, useful linear algebra, random number capabilities and Fourier transform.
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$$ What is Jupyter Notebook ? Introduction to Markdowns https://youtu.be/IdakPcu75ho

$$ Numpy Data Science Create Arrays Using NumPy Methods and Python Structures - https://youtu.be/69ComsKKRvA

$$ NumPy Indexing and Slicing Arrays, Boolean Mask Arrays , Numpy Python Data Science - https://youtu.be/z4vDLNMDFE4
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