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Alternatives

Products that do what I created a Neural Network from scratch, in scratch does

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.

  1. 1TA
  2. 2TB
  3. 3N5
  4. 4IT
  5. 5NN
  6. 6
    Sonnet134

    A new library for constructing neural networks from DeepMind

    2017

  7. 7IM

    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

  8. 8IW

    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

  9. 9NN
  10. 10W1

    Hey HackerNews, I built this project over the last few weeks as a palette cleanser from a failed game launch. I wanted to learn a bit about AI/Neural-Networks and naively thought I could build a tiny maze-solving AI in a weekend with a 100% solve rate. Well - I couldn't, but I got pretty close. 14 Bytes total model size, and a 96.5% solve rate on unseen mazes. Trained across 46 phases experimenting with different ideas to improve the model (better performance, smaller size). Its quite fun to watch the model attempt to solve the maze, when they fail its usually due to getting stuck in a…

    Jul 2026 · con-dog.github.io

  11. 11AV
  12. 12IW
  13. 13BH

    Hello HN, I recently posted a work-in-progress paper, along with code necessary for replicating all its results, at: https://github.com/glassroom/heinsen_routing Among other things, the code in this repo outperforms Hinton et al.'s recent state-of-the-art result in visual recognition[0] while requiring fewer parameters and an order-of-magnitude fewer training epochs. Most of the original research we do at work tends to be either proprietary in nature or tightly coupled to internal code, so we cannot share it with the world. In this case, however, I was able to remove all…

    2019

  14. 14IW

    2017 · github.com

  15. 15WB

    Hey HN, After GPT-3 created waves in the tech industry, a lot of AI tools were emerging and with that, some AI website builders But the results seemed way too generic to us. It felt like the developers were rushing to catch the wave instead of building a proper tool We took our time, did months of RnD and finally came up with something better than what others in the market are doing. It’s got better design output. While it’s still in beta, I wanted to show HN what we did. Will appreciate the feedback when you guys try it out. Here is the link to signup for the beta:…

    2024 · dorik.com

  16. 16TN

    Hi guys, I’m excited to share an update on ReproModel, an open-source toolbox designed to streamline the testing and reproduction of machine learning models. I, like many of you, have really struggled with benchmarking and comparing models, from missing code, to opaque experiment parameters slowing the process. I decided to take matters into my own hands, and created a mini-toolbox in my free time to streamline the process. The goal is to reduce the time and effort spent on replicating experiments, enabling researchers to focus on innovation rather than setup. Knowing this task is not an…

    2024 · github.com

  17. 17TJ

    After 6 years of coding almost every day, I'm finally ready to show HN. There's a lot going on here, looking forward to your guy's feedback.

    Jul 2026 · jaclang.org

  18. 18IV

    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

  19. 19IB

    Hey all, I’ve been working on a project that aims to change how we approach learning new skills. The idea is simple — you can master any skill in 30 days using a personalized learning plan powered by AI and Notion. They keys: practice and discipline. How it works: You can fill out a Typeform, and our AI will create a customized 30-day program just for you. Structured learning: Each day, the system provides you with a clear task or lesson based on science-backed learning principles. Track progress: It’s all managed in Notion, so you can stay organized and motivated while learning. Why I built…

    2025 · 30daysmethod.com

  20. 20IB

    Hello everyone, I doubt this would be relevant to the kind of person who uses HN, but I thought I could share for some feedback. I built this site because there is a whole world of people who believe in new age spirituality and I am very much one of them. It is a site where you get the users gender their goals and their images and use AI and psychology to generate images of them in the process of achieving their goals. I am so deeply struggling with how to get this highly on Google. I don't even know if that is important anymore. What are your suggestions with distribution and getting in…

    2025 · visionboardsai.com

  21. 21IB

    Fully leaned into vibe coding this time around. Started on v0, at some point ejected into running locally (getting v0's exported folder to run locally was a challenge), then iterated with Cursor over the course of a few hours. Really neat how much can be accomplished just conversationally these days.

    2025 · macrodata-refinement.arjit.me

  22. 22IB

    I've been experimenting with ways to increase AI adoption for non-technical people. Basically, all companies are pushing for AI because it's all over the news and they feel left behind but most people have no clue where to start. I think 90% of people (ie non coders) are sufficiently well served by using cowork instead of claude code or something similar. If we can get people from sales, customer support, marketing, etc to collaborate with skills and cowork to form a company brain, I think it's gold. So I think there's opportunity for the community to share skills that work well for 1000s of…

    Jun 2026 · claudinho.xyz

  23. 23CW

    Hey HN friends, Just launched my first NoCode web app, maching.ai, built with Bubble. Check it out and let me know if you have any questions or suggestions!

    2023 · maching.ai

  24. 24MA

    I've been working on training this small vision language model for the last month - excited to release the first prototype today! It is based on SigLIP (image encoder), Phi-1.5 (text model) and trained using the LLaVa-1.5 training dataset. It runs reasonably fast on CPU with ~8GB of RAM in full 32-bit precision. There's plenty of room to speed it up and reduce memory consumption by quantizing the model. I posted a video of it running on my M2 Macbook Air (on CPU not MPS, so performance should be comparable on other hardware) on Twitter to demonstrate inference speed:…

    2023 · github.com

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