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cprimozic.net
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| | | | | Introduces a browser-based sandbox for building, training, visualizing, and experimenting with neural networks. Includes background information on the tool, usage information, technical implementation details, and a collection of observations and findings from using it myself. | |
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golb.hplar.ch
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| | | | | [AI summary] The article describes the implementation of a neural network in Java and JavaScript for digit recognition using the MNIST dataset, covering forward and backpropagation processes. | |
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kevinlynagh.com
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| | | | | [AI summary] The author discusses their experience developing a simple neural network for sensor data processing on a microcontroller, highlighting challenges with quantization and inference optimization. | |
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jaketae.github.io
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| | | Recently, a friend recommended me a book, Deep Learning with Python by Francois Chollet. As an eager learner just starting to fiddle with the Keras API, I decided it was a good starting point. I have just finished the first section of Part 2 on Convolutional Neural Networks and image processing. My impression so far is that the book is more focused on code than math. The apparent advantage of this approach is that it shows readers how to build neural networks very transparently. It's also a good introduction to many neural network models, such as CNNs or LSTMs. On the flip side, it might leave some readers wondering why these models work, concretely and mathematically. This point notwithstanding, I've been enjoying the book very much so far, and this post is... | ||
