Numpy Attributes

Welcome to this in-depth guide on NumPy array attributes! 🎯 Whether you're a beginner or an experienced Python user, understanding these attributes will help you work efficiently with arrays in data analysis, scientific computing, and machine learning.

In this video, we’ll cover essential NumPy attributes with practical examples:

✔️ ndim – Number of dimensions in an array 📏
✔️ shape – Tuple representing the size of each dimension 📐
✔️ size – Total number of elements in the array 🔢
✔️ dtype – Data type of array elements 🔍
✔️ itemsize – Memory occupied by a single element in bytes 💾

🔎 Why are these attributes important?
✅ Helps in optimizing memory usage & performance
✅ Crucial for reshaping and manipulating arrays
✅ Essential for deep learning, image processing & large datasets

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Видео Numpy Attributes канала Knowledge Greenery