## MINST experiments

Please understand, this post is currently just a series of notes to myself, and I feel and learn my way through neural network programming. It is not a stand alone…

## Splitting arrays

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]])…

## Keras implementation of an LSTM neural network to classify and predict the MINST dataset

This started as an experiment to see whether an LSTM network, which is usually used to classify time series data, could be used to classify 2D data, for example, images…

## One Hot Encoding – OneHotEncoder()

Categorical data contains data that are labels as opposed to numerical values. One hot encoding Is a method to convert categorical data to numerical data. from numpy import array from…

## Numpy reshape() and arange()

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,…

## Normalising training and test data for neural networks

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…

## Effect of learning rate on training a neural network

I've just been playing around with learning rates on a data set, using a validation set to give me 'loss' and 'val_loss' outputs. I will include different learning rates and…

## Comparing values in a numpy array – all() and any()

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…

## IOPub data rate exceeded. The notebook server will temporarily stop sending output to the client in order to avoid crashing it.

I found a rather nice error pop up in my Jupyter notebook whilst playing around. After reading about this on the internet, I think I've fixed it. I'm using windows…