    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

## Derivative of a function of a function
Imagine a function
$$
f=y^2
$$
where $y$ is itself:
$$
y=x^3+x
$$

We can write this as $f = (x^3 + x)^2$ if we want to. 

How does $f$ change with $y$? That is, what is $\partial f / \partial y$? This is easy as we just apply the power rule we just developed, multiplying and reducing the power, so $\partial f / \partial y= 2y$.

How does $f$ change with $x$? Well, we could expand the expression $f = (x^3 + x)^2$ and apply this same approach. We can't apply it naively to $(x^3 + x)^2$ to become $2(x^3 + x)$. 

If we did many of these the long, hard way, using the diminishing deltas approach like we used before, we'd stumble upon another set of patterns. Let's jump straight to the answer. 

The pattern is this:
$$
\frac{\partial f}{\partial x} = \frac{\partial f}{\partial y} \cdot \frac{\partial y}{\partial x}
$$

# Derivative of a function of a function
Imagine a function
$$
f=y^2
$$
where $y$ is itself:
$$
y=x^3+x
$$

We can write this as $f = (x^3 + x)^2$ if we want to. 

How does $f$ change with $y$? That is, what is $\partial f / \partial y$? This is easy as we just apply the power rule we just developed, multiplying and reducing the power, so $\partial f / \partial y= 2y$.

How does $f$ change with $x$? Well, we could expand the expression $f = (x^3 + x)^2$ and apply this same approach. We can't apply it naively to $(x^3 + x)^2$ to become $2(x^3 + x)$. 

If we did many of these the long, hard way, using the diminishing deltas approach like we used before, we'd stumble upon another set of patterns. Let's jump straight to the answer. 

The pattern is this:
$$
\frac{\partial f}{\partial x} = \frac{\partial f}{\partial y} \cdot \frac{\partial y}{\partial x}
$$

Learn the chain rule of differentiation for functions.

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

Chain Rule

Derivative of a function of a function