NumPy Vectorization
Explore the concept of vectorization in NumPy and how it transforms traditional object-oriented and procedural Python approaches into faster, more efficient array operations. Understand the benefits of using NumPy for high-performance computing and how vectorized code reduces computation time drastically. This lesson helps you grasp fundamental techniques of vectorizing algorithms to enhance data processing speed in Python.
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Vectorization, in simple words, means optimizing the algorithm so that it can run multiple operations from a single instruction. NumPy is all about vectorization. If you are familiar with Python, this is the main difficulty you’ll face because you’ll need to change your way of thinking and your new friends (among others) are named “vectors”, “arrays”, “views” or "ufuncs".
Note: A custom magic command timeit is used in all codes. It’s a tool for measuring the execution time of small code ...