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dennybritz.com | ||
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datadan.io
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| | | | | Linear regression and gradient descent are techniques that form the basis of many other, more complicated, ML/AI techniques (e.g., deep learning models). They are, thus, building blocks that all ML/AI engineers need to understand. | |
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blog.ephorie.de
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| | | | | [AI summary] The blog post explores the connection between logistic regression and neural networks, demonstrating how logistic regression can be viewed as the simplest form of a neural network through mathematical equivalence and practical examples. | |
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sirupsen.com
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| | | | | [AI summary] An educational guide explaining how to build a neural network from scratch using Python, covering concepts like layers, gradient descent, autograd, and activation functions. | |
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saturncloud.io
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| | | By combining Dask and PyTorch you can easily speed up training a model across a cluster of GPUs. But how much of a benefit does that bring? This blog post finds out! | ||
