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AI · alternatives · 2026

Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. I wrote my first Neural Network launched in 2017; newer entries below may have overtaken it.

  1. 1

    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 →

  2. 2
    Sonnet▲134

    A new library for constructing neural networks from DeepMind

    2017 · deepmind.google · its alternatives →

  3. 3II
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  5. 5IC

    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 →

  6. 6

    An In-depth Visual Introduction For Beginners

    2017 · amazon.com · its alternatives →

  7. 7IM
  8. 8AV

    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 →

  9. 9

    The only shortcut David's learned after 5 startups? Learning

    2016 · soundcloud.com · its alternatives →

  10. 10

    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 →

  11. 11

    A Visual Introduction For Beginners

    2017 · amazon.com · its alternatives →

  12. 12

    The Mathematics of Neural Networks

    2017 · amazon.com · its alternatives →

  13. 13

    A Command-Line Program of Feedforward Neural Networks - dongyx/lnn

    2023 · github.com · its alternatives →

  14. 14

    Visualizing level surfaces of a neural network

    2017 · arogozhnikov.github.io · its alternatives →

  15. 15IA

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

    2018 · enlight.nyc · its alternatives →

  16. 16

    A Neural Network Playground

    2016 · playground.tensorflow.org · its alternatives →

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  18. 18IS
  19. 19

    Build neural networks from scratch and truly understand deep learning!

    2019 · manning.com · its alternatives →

  20. 20IB
  21. 21IV

    The video is here: https://www.youtube.com/watch?v=Ohs6sgmVNYI This video is a prof of concept. I always wanted to see if I could make my Neural Network play tinder for me. So I gather some pictures, created a fake tinder app (so I don't expose real people) and began the training. For this experiment I'm using scrcpy to control my cellphone and pyautogui alongside my neural network. The script is very simple: Get the image, run it trough a neural network, move the mouse to the output (yes or no) and click. There's a lot of hard coded things in my code, but as I said earlier,…

    2019 · its alternatives →

  22. 22

    Tensors and dynamic neural networks in Python

    2017 · pytorch.org · its alternatives →

  23. 23AS

    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

    2016 · aimatters.wordpress.com · its alternatives →

  24. 24IB

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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 →