Deep Learning / Neural Nets

Topics / Content

In this course, we will learn about the basics of deep learning and neural networks with a few parallel coding examples (and the corresponding theory) for some different types, e.g. Computer Vision, LLM, etc.

This course is meant for people that are beginners regarding deep neural networks, or want to know more about them / code their own one. We'll need some math, and coding basics (for this course python would be great).

If you never tried to code just a little, you can look into The Python Minibook

I will try to add as many examples as possible, because I think that "theory will get you only so far".

As I will (for the beginning) not dive deep into all the types of NNs (we'll only scratch the surface), and also maybe skip some types, I will add a "Further Reading" section from time to time.

The course will be separated into blocks, and these in little articles.

Just for your orientation a little example: The Block "Basics of Neural Networks" is separated into a few articles, visible in the description: "Basics of Neural Networks 01".

I will try to add a Content section to the beginning of all articles, so you can check quick if it's really the article you're searching for.

I recommend reading the whole course in a chronological order, especially the articles of one block, because they build up on each other.

You can skip whole topics/blocks, if you are not interested in them, but some blocks may introduce something new that will be important afterwards.

Basic Information

To be honest, I don't know much about Deep Learning currently, but I hope to learn much more while writing this course.

If you have problems understanding something, please open an Issue or write me an Email at kurt.schambach@gmail.com. I will try to fix any unclear parts.

Same with spelling mistakes, I have Issue Templates (for those who know github, and have an account), so you basically just have to fill out a little form. Also I will add a link for opening issues on every site (not mobile), so you won't have to come back here or search for my GitHub to open an Issue ;)

Edit: The buttons on the bottom right (not on mobile) are from the top:

• Link to the code
• Link for reporting a Bug or any kind of malfunction (you'll need a GitHub account for that)
• Link for reporting spelling mistakes (Also GitHub account needed)

If you don't have a GitHub account, just write me an informal Email.

Thank you for helping me improve the articles!

Course Overview

This overview is not final.

Basics of Neural Networks

• Our Brain and the Perceptron
• MNIST, and why good data is so important
• Structure of a Neural Network
• A Neural Network is learning
• Backpropagation - in progress

Computer Vision 1 - Introduction of many Tools we will use, and a first little NN

idk exactly rn, but sth like matplotlib, numpy, keras and tensorflow...

NLP / LLM

I'll add an overview soon

... more on the way