# NumPy Tutorials and Examples for Beginners NumPy is a Python package which stands for ‘Numerical Python’. It is the core libraryfor scientific computing, which contains a powerful n-imensional array object, providetools for integrating C, C++ etc.

In this page, we have written some numpy tutorials and examples, you can lean how to use numpy easily.

## Understand numpy.random.shuffle(): Randomly Permute a Sequence – Numpy Tutorial

numpy.random.shuffle() function can help us to permute a sequence randomly along the first axis , in this tutorial we will introduce how to use this function correctly.

## Understand numpy.random.permutation(): Randomly permute a sequence – Numpy Tutorial

numpy.random.permutation() can return a sequence randomly, which is very helpful in random two or more sequences. In this tutorial, we will introduce how to use this function correctly.

## Understand numpy.full(): Create an Array with Given Shape and Value – NumPy Tutorial

numpy.full() function can allow us to create an array with given shape and value, in this tutorial, we will introduce how to use this function correctly.

## A Basic Numpy Data Types List for Beginners – Numpy Tutorial

Numpy data type is called dtype, in this tutorial, we will list some common used numpy data types, which is much richer than python standard data types.

## Understand numpy.logspace() Function for Beginners – NumPy Tutorial

numpy.logspace() function can generate geometric series based on base( such as base = 10.0). In this tutorial, we will write some examples to show you how to use this function correctly.

## Best Practice to NumPy Create Hilbert Matrix for Beginners – NumPy Tutorial

Hilbert matrix is highly ill-conditioned matrix, in this tutorial, we write an python function to generate a hilbert matrix with numpy, you can use this function in your machine learning model.

## Understand numpy.newaxis with Examples for Beginners – NumPy Tutorial

numpy.newaxis represents a new axis in numpy array, in this tutorial, we will write some examples to help you understand how to use it correctly in python application.

## Understand Difference Between Python random.randint() and numpy.random.randint() – Python Tutorial

To generate a random integer, we can use python random.randint() and numpy.random.randint(), however, they are different. In this tutorial, we will discuss the difference between them.

## Best Practice to Calculate Cosine Distance Between Two Vectors in NumPy – NumPy Tutorial

Cosine distance is often used as evaluate the similarity of two vectors, the bigger the value is, the more similar between these two vectors. In this tutorial, we will introduce how to calculate the cosine distance between two vectors using numpy, you can refer to our example to learn how to do.

## Calculate Spearman’s Correlation Coefficient for Beginners – NumPy Tutorial

Spearman’s Correlation Coefficient is widely used in deep learning right now, which is very useful to estiment the correlation of two variables. In this  tutorial, we will introduce how to calculate spearman’s correlation coefficient.