Tensor NN Tutorials

The invention of Neural Networks is perhaps one of the most important in all computing history. Powering everything, in every industry, from cancer identification and DNA testing, to manufacturing, engineering and ChatGPT, Neural Networks are everywhere, and in this series of tutorials, I aim to give you a tour of the topic.

There are drop-down sections that include the mathematics used in neural networks. You can still complete the tutorials without reading these sections, but I highly recommend at least trying to read and understand those sections. I have given all of the maths sections difficulty ratings based on how complex the maths is: Easy (◈◇◇), Medium (◈◈◇) and Hard (◈◈◈). If you do decide to read these sections, please make sure that you have read the previous maths bits, as the knowledge carries over.

If you hover over purple dotted words, a definition or explanation will appear above the word. You can also hover above "Explain the Equation" for some equations to get a step-by-step explanation of what the formula is actually doing.

If you have never heard of, or have limited knowledge about neural networks, begin with "Introduction to Neural Networks"