NumPy Learning Repository

Welcome to the NumPy Learning Repository! This repository contains various Jupyter notebooks covering fundamental and advanced NumPy topics.

User Guide 👀

📌 NumPy Overview

✅ NumPy is a third-party Python module designed to work with arrays and matrices.
✅ NumPy stands for Numerical Python.
✅ It is open-source and widely used in scientific computing.
✅ It supports large multidimensional arrays & matrices.
✅ NumPy provides many mathematical functions to efficiently manipulate these elements.

💡 NumPy is an essential library for data science, machine learning, and numerical computing! 🚀

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✨ Why Use NumPy Arrays?

🔹 Consumes Less Memory
🔹 Much Faster compared to Python lists
🔹 Easy to Use
🔹 Supports Element-Wise Operations
🔹 Elements Are Stored Contiguously in Memory

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📌 Python Lists vs. NumPy Arrays

Python Lists

✔️ Homogeneous → Can contain the same type of objects.
✔️ Heterogeneous → Can contain different types of objects.

NumPy Arrays

🔹 All elements must be of the same type.
🔹 More memory-efficient → You can be sure about the storage size required.
🔹 Indexed from 0 (just like Python lists).

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📚 Exercises

• 100 NumPy Questions & Solutions (From numpy-100)
• Explore the exercises folder for practical examples and exercises to enhance your NumPy skills. The numpy_exercises.ipynb file contains various problems and solutions to help you practice and master NumPy.

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✅ This repository is a work in progress. Stay tuned for updates! 😊