This module explains how to build up a basic neural network step-by-step. It also uses the MNIST dataset for detecting numbers from handwriting.

Neural Networks: Beginners to Advanced

Machine learning is one of the fastest growing fields. This module aims to teach one of the fundamental concepts of machine learning, that is neural networks. You will learn the basic concepts of building a model as well as the mathematical explanation behind the neural network. You will learn to build the neural network from scratch, in Python. You will also learn how to train and optimize your network to achieve a better result. We’ve specifically designed this module for beginners so it doesn’t require any prior programming experience. Happy learning!

Make Your Own Neural Network in Python

## Code to plot data points 

We saw earlier how we might plot a rectangular array of numbers using the `imshow()` function. We want to do the same here, but we need to convert that list of comma-separated numbers into a suitable array. Here are the steps to do that:

1. Split that long text string of comma-separated values into individual values, using the commas as the place to do the splitting.

2. Ignore the first value and the label, and take the remaining list of $28 \times 28 = 784$ values and turn them into an array that has a shape of $28$ rows $\times$ $28$ columns.

3. Plot that array.

Again, it is easiest to show the simple Python code that does this and talk through the code to explain in more detail what is happening.

We must not forget to import the Python extension libraries first, which will help us with arrays and plotting:

# Code to plot data points 

We saw earlier how we might plot a rectangular array of numbers using the `imshow()` function. We want to do the same here, but we need to convert that list of comma-separated numbers into a suitable array. Here are the steps to do that:

1. Split that long text string of comma-separated values into individual values, using the commas as the place to do the splitting.

2. Ignore the first value and the label, and take the remaining list of $28 \times 28 = 784$ values and turn them into an array that has a shape of $28$ rows $\times$ $28$ columns.

3. Plot that array.

Again, it is easiest to show the simple Python code that does this and talk through the code to explain in more detail what is happening.

We must not forget to import the Python extension libraries first, which will help us with arrays and plotting:

Learn how digits are formed by plotting some of the data points.

Prologue

Part 1 - A Little Background

Part 2 - Let's Get Started!

Part 3 - Backward Propagation of Error

Part 4 - Adjusting the Link Weights

Part 5 - A Gentle Start with Python

Part 6 - Neural Network with Python

Part 7 - Testing Neural Network against MNIST Dataset

Part 8 - Some Suggested Improvements

Part 9 - Even More Fun!

Appendix: A Small Guide to Calculus

Conclusion

Plot the Data Points

Code to plot data points