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Dev tools · alternatives · 2026

24 alternatives to Simple Neural Network

Simple way to learn neural network on C++

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. Simple Neural Network launched in 2023; newer entries below may have overtaken it.

  1. 1

    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 →

  2. 2

    Trying to understand neural nets by building a simple one from scratch - kretash/BasicNeuralNet

    2017 · github.com · its alternatives →

  3. 3
  4. 4AV

    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 →

  5. 5

    Simple and comprehensive tutorials in TensorFlow. Contribute to easy-tensorflow/easy-tensorflow development by creating an account on GitHub.

    2018 · github.com · its alternatives →

  6. 6N5
  7. 7

    A perceptron written in COBOL. Contribute to victorqribeiro/perceptronCobol development by creating an account on GitHub.

    2020 · github.com · its alternatives →

  8. 8

    A single / multi layer / recurrent neural network written in Golang. - made2591/go-perceptron-go

    2017 · github.com · its alternatives →

  9. 9

    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 →

  10. 10

    Neural network inference the Unix way. Contribute to cloudkj/layer development by creating an account on GitHub.

    2019 · github.com · its alternatives →

  11. 11IA

    An introduction to building a basic feedforward neural network with backpropagation in Python.

    2018 · enlight.nyc · its alternatives →

  12. 12

    :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 →

  13. 13

    A flexible artificial neural network builder to analyse performance, and optimise the best model. - GitHub - casparwylie/Perceptron: A flexible artificial neural network builder to analyse performance, and optimise the best model.

    2017 · github.com · its alternatives →

  14. 14
  15. 15

    A minimal viable programming language on top of liblgpp - codr7/alang

    2021 · github.com · its alternatives →

  16. 16
    MakeML▲274

    Train Neural Networks without a line of code

    2019 · makeml.app · its alternatives →

  17. 17

    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 →

  18. 18

    sketch-rnn model trained to write kanji.

    2018 · otoro.net · its alternatives →

  19. 19AB
  20. 20

    Trying to do gradient descent using automatic differentiation over branchy programs? Or to combine them with neural networks for end-to-end training? Then this might be interesting to you. We develped DiscoGrad, a tool for automatic differentiation through C++ programs involving input-dependent control flow (e.g., "if (f(x) < c) { ... }", differentiating wrt. x) and randomness. Our initial motivation was to enable the use of gradient descent with simulations, which often rely heavily on such discrete branching. The latter makes plain autodiff mostly useless, since it can only account for the…

    2024 · github.com · its alternatives →

  21. 21IM
  22. 22

    Arabic root finder with neural nets! Contribute to tb0yd/rootfinder development by creating an account on GitHub.

    2018 · github.com · its alternatives →

  23. 23

    Deep learning platform built for developers

    2018 · paperspace.com · its alternatives →

  24. 24

    Resumes generated by a neural network

    2019 · thisresumedoesnotexist.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 →