An introduction to neural networks
by Kevin Gurney · first published 1997
5mentions
3recommended by
5HN commenters
2014–2021first – last mentioned
60% recommend40% neutral
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The book I used to learn the basics many years ago was "An Introduction to Neural Networks", by Kevin Gurney. It's a bit outdated now, but I still consider it valuable.
on “Backpropagation 101 (2020)” ↗…number of cost functions you can use for the last layer - softmax or cross-entropy are other possibilities that may be easier to understand, though possibly less performant for NLP tasks. I thought the introduction to neural networks from Andrew Ng's coursera course (even though it meant writing MATLAB) was quite good, and allows you to implement backprop, cost functions, etc. while still having some other helper code to make things…
on “Deep Learning for NLP without Magic (2013)” ↗This is the most accessible introduction to Neural Networks I've found. The interactive bits really help as does the concrete example.
on “Show HN: A Visual and Interactive Guide to the Basics of Neural Networks” ↗…books don't interest me at all. If I wanted to learn some particular framework, I would just look up the documentation for that framework. I'm looking for two types of books: 1. A technical, math-heavy introduction to neural networks and deep learning, with little or no actual code (except possibly some pseudocode). The often recommended book by Goodfellow et al resembles what I'm looking for, but unfortunately, it completely lacks…
on “Ask HN: What Neural Networks/Deep Learning Books Should I Read?” ↗Hey, author here. Any/all feedback is welcome, and I'm happy to answer questions. Previous discussion on HN of the "introduction to Neural Networks" referenced in this article: https://news.ycombinator.com/item?id=19320217 Runnable code from the article: https://repl.it/@vzhou842/A-CNN-from-scratch-Part-1 Github: https://github.com/vzhou842/cnn-from-scratch
on “Implementing a Convolutional Neural Network from Scratch in Python” ↗