There are many different ways to split arrays, but commonly this method is used in creating training and testing sets in neural networks. from numpy import array a = array([[1,2,3,4,5],[6,7,8,9,10],[11,12,13,14,15],[16,17,18,19,20]])…
Just learning about these numpy functions that are useful in array manipulation (and creation). np.arrange The arange() function from numpy creates numeric sequences. It's syntax is as follows: np.arrange (start,…
A common mistake when using neural networks it would seem is to separately normalise training and test data. The following codes demonstrate how, as far as I know, this should…
import numpy as np # create a 2 dimentional array and put some values in myData = np.array([[1.1, 2.2, 3.3], [4.4, 5.5, 6.6]]) print (myData.shape) print (myData[0,1]) print (myData[1,1]) if…
Given the following code: # import required to process csv files with pandas import pandas as pd #for array manipulation import numpy as np # use pandas to import a…
In this post I'm going to be working out and learning out preparing data for LSTM networks, particularly data with several features. With LSTM networks we are able to deal…
The input to every LSTM network layer must be 3D. But what does this mean? Let's consider a sequence of multiple time steps with 1 feature. This could be a…
Lists and arrays in Python are quite similar but they're certainly not the same. Let's create a list and an array in python and see the differences. Creating a list…