# NumPy & Python Crash Course

NumPy is a powerful library in Python for numerical computation and manipulation. It provides several functions for working with arrays, matrices, and mathematical operations.

The main data structure in NumPy is the array, which is a multi-dimensional grid of elements of the same data type. Arrays can be used for various mathematical operations, such as linear algebra and Fourier transformation.

NumPy provides several functions for working with arrays, such as:

**Array creation**: NumPy provides functions for creating arrays, such as creating an array from a list or creating an array of zeros or ones.

**Array manipulation**: NumPy provides functions for manipulating arrays, such as reshaping, slicing, and concatenating arrays.

**Array computation**: NumPy provides functions for computing with arrays, such as mathematical operations and linear algebra.

**Array visualization**: NumPy can be used with other visualization libraries such as Matplotlib, which allows you to create various types of plots and charts to visualize arrays.

In summary, NumPy is a powerful library in Python for numerical computation and manipulation. It provides several functions for working with arrays, matrices, and mathematical operations. The main data structure in NumPy is the array, which is a multi-dimensional grid of elements of the same data type. NumPy provides several functions for working with arrays, such as creation, manipulation, computation and visualization.

In this Applied Machine Learning Recipe, the reader will learn: NumPy & Python Crash Course.

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