`NumPy` offers a variety of functions for **saving** and **loading** `numPy` arrays to and from files, such as:
- **`save()`**: Saves an array to a binary file in `NumPy`'s **`.npy`** format;
- **`savez()`**: Saves multiple arrays to a single compressed **`.npz`** file;
- **`savetxt()`**: Saves an array to a text file;
- **`load()`**: Loads an array from a binary file in `NumPy`'s **`.npy`** format;
- **`loadtxt()`**: Loads an array from a text file.

## Congratulations!

Congratulations on completing this `NumPy` tutorial! You have gained substantial knowledge about handling arrays and matrices in Python, laying down a strong foundation for utilizing `NumPy` in your data processing and analysis endeavors.

In this project, we will delve into the fundamentals of NumPy, exploring its core features and uncovering the reasons behind its significant impact on scientific computing. By understanding its architecture and capabilities, we will grasp why it is considered an essential tool for data scientists, researchers, and developers working in the realm of data analysis, machine learning, and beyond.

In this project, we will delve into the fundamentals of NumPy, exploring its core features and uncovering the reasons behind its significant impact on scientific computing.

Getting into NumPy Basics

Saving and Loading Arrays to/from Files

Congratulations!