What exactly is an artificial neuron

Hi @bbos

thanks for your question.

Please have a look at a graphical visualization which contains the relevant elements:

see also: Choice of activation function - #8 by Christian_Simonis

In the end we can use ground truth data (labels) to fit the neural network. So the purpose is always that the model learns the model parameters during the fitting (which serves an optimization to model the labels well) so that the model learns abstract patterns sufficiently and generalizes well to predict the label, also on new / unseen data of course.

In reality this prediction has to be „good enough“ to solve the business problem, see also: How does a Deep Neural Network work? - #4 by Christian_Simonis

I think if you want to dive deeper with more practice and technical depth, you could consider other courses to follow-up after AI4everyone, see also: Please help with course selection - #2 by Christian_Simonis

A quite classic sequence which seems to be popular among fellow learners seems to be:

  • AI for everyone (if you are a beginner)
  • machine learning specialization for the basics and core concepts
  • deep learning specialization if this suits your plans and you work rather with big unstructured data and want to apply or work with CV, NLP, LLM etc.
  • (MLOps, LLM specialization or TF specialization dependent on your requirements and plans)

Hope that helps!


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