1. Machine Learning for Beginners: An Introduction to Neural Networks
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A simple explanation of how they work and how to implement one from scratch in Python.
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This 4-post series, written especially with beginners in mind, provides a fundamentals-oriented approach towards understanding Neural Networks. We’ll start with an introduction to classic Neural Networks for complete beginners before delving into two popular variants: Recurrent Neural Networks (RNNs) and Convolutional Neural Networks (CNNs).
For each of each these types of networks, we’ll:
This series requires ZERO prior knowledge of Machine Learning or Neural Networks. However, background in the following topics may be helpful:
Ready to get started? Here we go:
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A simple explanation of how they work and how to implement one from scratch in Python.
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A simple walkthrough of what RNNs are, how they work, and how to build one from scratch in Python.
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A simple guide to what CNNs are, how they work, and how to build one from scratch in Python.
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A simple walkthrough of deriving backpropagation for CNNs and implementing it from scratch in Python.
Still eager to learn? Some more things you can do include:
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