    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.

Make your own neutral network in python final.png

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

## How computers understand information
Computers are nothing more than calculators at heart. They are very fast at doing arithmetic. This is great for tasks that match what a calculator does—summing numbers for sales, applying percentages to work out taxes, and plotting graphs of existing data.

Even watching catch-up TV or streaming music through your computer doesn’t involve much more than the computer executing simple arithmetic instructions again and again. It may surprise you, but reconstructing a video frame from the 1s and 0s that are piped across the internet to your computer is done using arithmetic that isn't much more complex than the sums we did in school. 

Adding up numbers really quickly—thousands, or even millions of numbers a second—may be impressive, but it isn’t artificial intelligence. A human may find it hard to do large sums very quickly, but the process of doing it doesn’t require much intelligence at all. It simply requires an ability to follow very basic instructions, and this is what the electronics inside a computer do.

Now let’s flip things and turn the tables on computers! Let's look at the following images and see if we can recognize what they contain.


# How computers understand information
Computers are nothing more than calculators at heart. They are very fast at doing arithmetic. This is great for tasks that match what a calculator does—summing numbers for sales, applying percentages to work out taxes, and plotting graphs of existing data.

Even watching catch-up TV or streaming music through your computer doesn’t involve much more than the computer executing simple arithmetic instructions again and again. It may surprise you, but reconstructing a video frame from the 1s and 0s that are piped across the internet to your computer is done using arithmetic that isn't much more complex than the sums we did in school. 

Adding up numbers really quickly—thousands, or even millions of numbers a second—may be impressive, but it isn’t artificial intelligence. A human may find it hard to do large sums very quickly, but the process of doing it doesn’t require much intelligence at all. It simply requires an ability to follow very basic instructions, and this is what the electronics inside a computer do.

Now let’s flip things and turn the tables on computers! Let's look at the following images and see if we can recognize what they contain.


Compare a biological mind and a scientific mind.

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

Humans vs. Computers

How computers understand information