Softmax function is widely used in deep learning classification problem. This function may cause underflow and overflow problem. To avoid these problems, we will use an example to implement softmax function.
numpy.split() can allow us to split a numpy array into some sub-arrays, however, there are some notices you must concern when you are using this function. In this tutorial, we will some examples to discuss these notices.
We have to check our numpy version when our numpy is imcompatible with other python packages. How to check in python? In this tutorial, we will use a simple example to tell you how to do.
There are three multiplications in numpy, they are np.multiply(), np.dot() and * operation. In this tutorial, we will use some examples to disucss the differences among them for python beginners, you can learn how to use them correctly by this tutorial.
When you are using numpy.savetxt() function to save numy array into a text file, you my get this error: TypeError: Mismatch between array dtype (‘
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.