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.

Saving a numpy array to csv file can help us to share data for others or other python applications. In this tutorial, we will talk about some tips on how to save.

numpy.savetxt() function can help us to save numpy data into a txt file (.txt or .csv). In this tutorial, we will write some examples to help numpy beginners to undstand and use it correctly.

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.

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.

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.

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.

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.

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.

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.

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