    Gain insights into building and optimizing neural networks in Python. Delve into fundamental concepts, mathematical explanations, and practical implementations to enhance your machine learning skills.

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Machine learning is one of the fastest growing fields, and we cannot emphasize enough about its importance. This course aims to teach one of the fundamental concepts of machine learning, i.e., Neural Network. You will learn the basic concepts of building a model as well as the mathematical explanation behind Neural Network and based on that; you will build one from scratch (in Python). You will also learn how to train and optimize your network to achieve a better result.

Make Your Own Neural Network in Python

## Open the dataset 
Before we can do anything with the data, like plotting it or training a neural network with it, we need to find a way to get at it from our Python code.

Opening a file and getting its content is easy in Python. Let's look at the following code:


# Open the dataset 
Before we can do anything with the data, like plotting it or training a neural network with it, we need to find a way to get at it from our Python code.

Opening a file and getting its content is easy in Python. Let's look at the following code:


Explore how to access and use the dataset file in Python.

Prologue

A Little Background

Let's Get Started!

Backward Propagation of Error

Adjusting the Link Weights

A Gentle Start with Python

Neural Network with Python

Testing Neural Network against MNIST Dataset

Some Suggested Improvements

Even More Fun!

Epilogue

Appendix: A Small Guide to Calculus

Get the Dataset Ready

Open the dataset