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NumPy Series: From Fundamentals to Real-World Applications

Welcome to the NumPy Learning Series – a structured repository for mastering NumPy, the fundamental package for scientific computing with Python. This series is designed to take you from beginner-level array manipulations to working with real-world data and images

🚀 Prerequisite

Before diving into this series, ensure you have:

  • A basic understanding of Python (variables, loops, functions, etc.)
  • Python 3.x installed
  • numpy, matplotlib, and Pillow libraries installed (pip install numpy matplotlib Pillow)

📚 Series Outline

✅ Phase 1: NumPy Foundation

  • Understanding what NumPy is and why it's used

  • Creating NumPy arrays

  • Basic properties and attributes of arrays

  • Common array creation methods: zeros(), ones(), arange(), linspace(), etc.

  • ✅ Phase 2: Operations on NumPy Arrays

  • Indexing, slicing, and iterating

  • Mathematical operations

  • Aggregations: sum(), mean(), std(), etc.

  • Broadcasting and vectorized operations

  • ✅ Phase 3: Practice with Real-World Data

  • Working with real datasets (CSV/TSV files)

  • Using NumPy for data preprocessing

  • Data cleaning and basic analytics with NumPy arrays.

  • ✅ Phase 4: Image as Matrix

  • Representing images as NumPy arrays

  • Reading and displaying images using Pillow and matplotlib

  • Converting images to Dark Mode using NumPy operations