    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

# Neurons and how they work
We said earlier that animal brains puzzled scientists, because even small ones like pigeon brains were vastly more capable than digital computers with large quantities of electronic computing elements and storage space running at frequencies much faster than fleshy, squishy natural brains.

Because of this, scientists began paying attention to the architectural differences between the two kinds of brains. Traditional computers processed data sequentially and in fairly exact concrete terms. There was no fuzziness or ambiguity about their calculations. Animal brains, on the other hand, although apparently running at much slower rhythms, seemed to process signals in parallel, and fuzziness was a feature of their computation. Let’s look at the basic unit of a biological brain—the neuron.

Compare neurons in human brains to digital computer resources.

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

Neurons: Nature’s Computing Machines

Neurons and how they work