AI News, BOOK REVIEW: A Beginner’s Guide to Neural Networks in Python and SciKit Learn 0.18

A Beginner’s Guide to Neural Networks in Python and SciKit Learn 0.18

Neural Networks are a machine learning framework that attempts to mimic the learning pattern of natural biological neural networks: you can think of them as a crude approximation of what we assume the human mind is doing when it is learning.

Biological neural networks have interconnected neurons with dendrites that receive inputs, then based on these inputs they produce an output signal through an axon to another neuron.

We must also make sure to add a bias to the perceptron, a constant weight outside of the inputs that allows us to achieve better fit for our predictive models.

Once we have the output we can compare it to a known label and adjust the weights accordingly (the weights usually start off with random initialization values).

To create a neural network, we simply begin to add layers of perceptrons together, creating a multi-layer perceptron model of a neural network.

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