Coding a Neural Network: A Beginner's Guide (part 2)

Neural networks simplified and made easy, for the layperson (or medical practitioner). I've tried to keep things simple, and provide a beginner's introduction to machine learning and neural networks. By the end of this series, you'll have created your first complete and functioning artificial neural network, written in Google Colab. I recommend listening on 1.5 or 2x speed.

Part 2 is all about generating a 'loss function', which will help us determine how poor our network's predictions probably were.

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Let me know what you think in the comments below👇

[bartlomiejkowalczyk]

amazing, do you have any course about deep learning?

[MWKnives]

Correct me if I'm wrong, but isn't the result of multiplying the result of the ReLU function by the second weights supposed to be o_nodes? You defined this variable in the context of making it align with the visual graphic. This should be the output of that computation, right? It gets a little confusing following you when you populate what is supposed to be the output of the network with random data. I think you simply meant to assign o_data instead of creating a whole new variable.

[yuveshragavendiran]

Very goood loved it.though it takes time, as ur videosare of great potential, they will get famous!!!