This repository contains my hands-on practice notebooks created using Google Colab as I learn and explore NumPy, the foundational Python library for numerical computing.
I'm learning NumPy as part of my preparation for real-world AI/ML projects, including medical applications like lung and brain cancer detection. These Colab notebooks help me:
- Build strong fundamentals
- Document everything I practice
- Quickly refer back during future projects
- ✅ Importing NumPy and comparing speed with lists
- ✅ Creating 1D and 2D arrays
- ✅ Arrays of 0s, 1s, identity matrix
- ✅ Arrays with specific values and data types
- ✅ Random floats and integers
- ✅ Evenly spaced values (
arange,linspace) - ✅ Array operations: add, subtract, multiply, divide
- ✅ Transpose, reshape, flatten
- ✅ Array info: shape, size, ndim, dtype
🔜 Coming Soon:
- Indexing and slicing
- Boolean filtering
- Broadcasting
- Stacking and concatenation
- 🧪 Python 3.x
- 📚 NumPy
- ☁️ Google Colab
numpy1.ipynb– Main notebookREADME.md– Project description
📺 Learned from Youtube Channel: [Siddhardhan]
This is a self-learning project. If you're also learning NumPy, feel free to explore, clone, or suggest improvements!