AI · alternatives · 2026
24 alternatives to A simple neural network in Octave to solve the XOR problem
Getting started with neural networks can seem to be a daunting prospect, even if you have some programming experience. The many examples on the Internet dive straight into the mathematics of what the neural network is doing or are full of jargon that can make it a little difficult to understand what
Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Prices are shown for the 1 we have checked on their own sites, 1 of them free or with a free tier. A simple neural network in Octave to solve the XOR problem launched in 2016; newer entries below may have overtaken it.
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The simplest form of an artificial neural network explained and demonstrated. - GitHub - gokadin/ai-simplest-network: The simplest form of an artificial neural network explained and demonstrated.
2020 · github.com · its alternatives →
- 2AV
Discussions: Hacker News (63 points, 8 comments), Reddit r/programming (312 points, 37 comments) Translations: Arabic, French, Spanish Update: Part 2 is now live: A Visual And Interactive Look at Basic Neural Network Math Motivation I’m not a machine learning expert. I’m a software engineer by train
2016 · jalammar.github.io · its alternatives →
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2024 · graphgame.sabrina.dev · its alternatives →
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I've been a longtime member @ HN, but I haven't been a developer. In fact, my only HN submission has been one asking how to learn to code (http://news.ycombinator.com/item?id=820741). My cofounder and I decided to solve the problem by making a simple, interactive way to get started with Codecademy. We'd love your feedback. If you're interested in helping us to get more courses up (on any topic!), please send us an email at [email protected].
2011 · codecademy.com · its alternatives →
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:satellite: Simple and ready-to-use tutorials for TensorFlow - GitHub - instillai/TensorFlow-Course: :satellite: Simple and ready-to-use tutorials for TensorFlow
2018 · github.com · its alternatives →
- 6IA
An introduction to building a basic feedforward neural network with backpropagation in Python.
2018 · enlight.nyc · its alternatives →
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Simple and comprehensive tutorials in TensorFlow. Contribute to easy-tensorflow/easy-tensorflow development by creating an account on GitHub.
2018 · github.com · its alternatives →
- 8IM
2017 · neuralnetsforhackers.teachable.com · its alternatives →
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A ranked ladder for small neural networks that play strategy games. Train a model, write an adapter, upload two files, and get measured into a weight class from 8 KiB up.
Sep 2026 · tinybrains.dev · its alternatives →
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I have been interested in neural nets since the 90's. I've done quite a bit of reading, but never gotten around to writing code. I used Gemini in place of Wikipedia to fill in the gaps of my knowledge. The coolest part of this was learning about dual numbers. You can see in early commits that I did not yet know about auto-diff; I was thinking I'd have to integrate a CAS library or something. Now, I'm off to play with TensorFlow.
Mar 2026 · github.com · its alternatives →
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Neural network inference the Unix way. Contribute to cloudkj/layer development by creating an account on GitHub.
2019 · github.com · its alternatives →
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I’m 15 and self-taught. I'm learning ML from scratch because I want to really understand how things work. I’m not into frameworks. I prefer math, logic, and C++. I implemented a basic MLP that supports different activation and loss functions. It was trained via mini-batch gradient descent. I wrote it from scratch, using no external libraries except Eigen (for linear algebra). I learned how a Neural Network learns (all the math) -- how the forward pass works, and how learning via backpropagation works. How to convert all that math into code. I’ll write a blog soon explaining how MLPs work in…
2025 · github.com · its alternatives →
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A perceptron written in COBOL. Contribute to victorqribeiro/perceptronCobol development by creating an account on GitHub.
2020 · github.com · its alternatives →
- 14AB
2015 · neurovis.dataphoric.com · its alternatives →
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Can a neural network learn to recognize doodles?
2016 · quickdraw.withgoogle.com · its alternatives →
- 16NX
More precisely, even the best neural networks can not be trained to approximate periodic functions using stochastic gradient descent. (empirically, prove me wrong!) Contents Simulating a clock Simplifying the problem Why can’t we train the sin? What to do about it? Simulating a clock The problem tha
2022 · lostmsu.github.io · its alternatives →
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Trying to understand neural nets by building a simple one from scratch - kretash/BasicNeuralNet
2017 · github.com · its alternatives →
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Arabic root finder with neural nets! Contribute to tb0yd/rootfinder development by creating an account on GitHub.
2018 · github.com · its alternatives →
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2015 · otoro.net · its alternatives →
- 20IC
I spent the past week implementing a 1 Layer Neural Net and training it on MNIST within the visual scripting language provided by scratch.mit.edu. It was tedious, but ultimately not too difficult. The code runs incredibly slowly, so much so that 64 samples of MNIST takes 5+ hours to train on my machine. There were a lot of little mini challenges that were fun to overcome (implementing softmax was very tricky). If you're interested, I encourage you to try and improve on it! More details in the linked blog post.
2024 · bell-boy.github.io · its alternatives →
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A single / multi layer / recurrent neural network written in Golang. - made2591/go-perceptron-go
2017 · github.com · its alternatives →
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:earth_americas: Simple and ready-to-use deep learning examples for the Microsoft Cognitive Toolkit (CNTK) - CNTK-World/README.rst at master · astorfi/CNTK-World
2017 · github.com · its alternatives →
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The Mathematics of Neural Networks
2017 · amazon.com · its alternatives →
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I'm a machine learning engineer and researcher. I got fed up with how difficult it is to understand why neural networks behave the way they do, so i wrote a library to help with it. Comgra (computation graph analysis) is a library you can use with pytorch to extract all the tensor data you care about and visualize it graphically in a browser. This allows for a much more detailed analysis of what is happening than the usual approach of using tensorboard. You can go investigate tensors as training proceeds, drill down into individual neurons, inspect single data sets that are of special…
2023 · github.com · its alternatives →
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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →