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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

## Training and testing with a full dataset
Previously, we added a simple code to work out the fraction of correct answers. Let’s see what this updated code produces:

# Training and testing with a full dataset
Previously, we added a simple code to work out the fraction of correct answers. Let’s see what this updated code produces:

Train and test the neural network with a full dataset and evaluate its performance.

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

Evaluate the Performance of the Neural Network

Training and testing with a full dataset