Make your own neural networks from scratch in Python. Take it one step at a time!


From Scratch, Create Neural Networks in Python!

No prior software frameworks are required to understand machine learning principles such as linear regression, gradient descent, and deep learning.

What you'll discover

Using Python, you can create your own neural networks from the ground up.

Become familiar with the principles of neural networks.

Basic Python skills are required to build neural networks.

You'll learn about feedforward, backward propagation, gradient descent, and regression in a step-by-step manner.

Learn how to use Softmax, ReLU, and Sigmoid to estimate complex non-linear prediction functions.

Consider neural networks as a mathematical construct that can be implemented in any language, including those that don't support libraries.


Neural networks captivate your attention.

Python or another programming language is familiar to you.

There will be no exercises in this course. Use the code examples as you choose in your own work.


Wunderlist for Windows and Microsoft To-Do are two of my most popular products; I really like teaching software development!

This course teaches you how to build neural networks using Python. Just a few lines of code may transform an ordinary neural network into a system that can read handwritten digits without the need for libraries. Some of the concepts you'll learn about in this process include feedforward, cost backpropagation, hidden layers, linear regression, gradient descent and matrix multiplication.

There is a logical progression from one subject to another. Using this technique, you will learn how to design neural networks from scratch.

What sets this course apart from the rest?

In reality, many courses claim to start from scratch, but after importing external libraries or entering in code rapidly, you're gazing at 50 lines of code before you've even ran it. You're still puzzling over what line 3 means when the programme eventually runs.

First, I'm going backwards in time. Measures must be taken before we can accomplish our goals. As long as we do things step-by-step, it won't be a problem!'

After completing this course, my students say they have a greater grasp of neural networks and how they operate. After understanding the coding, they started from scratch and developed neural networks.

Developers who want to learn how to build neural networks from scratch without depending on frameworks.


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