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🚀 Course: NumPy (2.2.6) A-Z
🔁 Module 03: Broadcasting and IO
🧠 Lecture A: Broadcasting Rules

👇 Link to the notebook:
https://tinyurl.com/282z3z7b

🚀 NumPy broadcasting tutorial for data science: learn NumPy broadcasting rules, how shapes align from the right, and how size-one dimensions expand so you can combine scalars, vectors, and higher-dimensional arrays without loops. This lecture walks through practical Python examples of scalar and vector broadcasting, row and column offsets, featurewise normalization, batch image scaling, and real-world cases in finance, recommendation systems, and temperature grids. You will also learn to read broadcasting errors, use newaxis, and reshape arrays for compatibility. Watch to build an intuitive understanding of NumPy broadcasting and improve your numerical computing workflows.

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NumPy (2.2.6) A-Z | 03A

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