Life & fun · alternatives · 2026

24 alternatives to How to build your own Multilayer Perceptron with Golang

Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. How to build your own Multilayer Perceptron with Golang launched in 2017; newer entries below may have overtaken it.

1. 1
   A perceptron with stochastic gradient descent in Go▲94

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

   2017 · github.com · its alternatives →

2. 2
   Duplicate 3 layers in a 24B LLM, logical deduction .22→.76. No training▲265

   I replicated David Ng's RYS method (https://dnhkng.github.io/posts/rys/) on consumer AMD GPUs (RX 7900 XT + RX 6950 XT) and found something I didn't expect. Transformers appear to have discrete "reasoning circuits" — contiguous blocks of 3-4 layers that act as indivisible cognitive units. Duplicate the right block and the model runs its reasoning pipeline twice. No weights change. No training. The model just thinks longer. The results on standard benchmarks (lm-evaluation-harness, n=50): Devstral-24B, layers 12-14 duplicated once: - BBH Logical Deduction: 0.22 → 0.76…

   Mar 2026 · github.com · its alternatives →

3. 3
   GBrain▲120

   Plug your own memory, tools, and skills into any AI

   Sep 2026 · gbrain.io · its alternatives →

4. 4
   A basic generic multi layer perceptron▲8

   2014 · github.com · its alternatives →

5. 5
   Sonnet▲134

   A new library for constructing neural networks from DeepMind

   2017 · deepmind.google · its alternatives →

6. 6
   Muse Gadgets▲185

   Meta's open-source kit for building your own AI gadgets

   21d ago · gadgets.muse.ai · its alternatives →

7. 7
   Perceptron – Artificial Neural Network Builder▲61

   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 →

8. 8
   A Golang library to build Turing machine▲6

   2019 · made2591.github.io · its alternatives →

9. 9IC
   I co-wrote a book on training Deep Learning models in Go▲45

   A friend and I wrote a book on how to build and train Deep Learning models in Go. We wanted it to be a useful reference for deep learning basics for Go programmers. Deep Learning is slowly seeping into everything we use every day and we thought it would be great if more people could do it in Go. The book is available here and on Amazon as well. https://www.packtpub.com/big-data-and-business-intelligence/hands-deep-learning-go We would appreciate any feedback and we're always looking to improve.

   2019 · its alternatives →

10. 10
    A completely handwritten deep neural network in python▲13

    A handwritten multilayer perceptron classifer using numpy. - meetvora/mlp-classifier

    2016 · github.com · its alternatives →

11. 11
    Train a Convolutional Neural Nets Using Multi-Party Computation▲28

    Most efforts to privately train machine-learning models either use homomorphic encryption or secure multi-party computation (MPC). Recent insights indicate…

    2018 · blog.openmined.org · its alternatives →

12. 12
    Minigrad – a small neural network lib in Golang▲9

    I built a neural network library in golang on an autograd engine. Faster and easy to use like PyTorch. Please give it a try and share your feedback. if you like it, a github star will be appreciated.

    2024 · github.com · its alternatives →

13. 13
    33% Memory Reduction by Reordering Struct Fields▲19

    Learn Go (Golang) by writing real code in this interactive course. Practice structs, interfaces, errors, concurrency, and idiomatic backend patterns.

    2020 · qvault.io · its alternatives →

14. 14
    Perceptron Mk1▲26

    Frontier video reasoning for the physical world

    May 2026 · perceptron.inc · its alternatives →

15. 15IC
    I created a Neural Network from scratch, in scratch▲7

    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 →

16. 16
    Make Your Own Neural Network▲6

    An In-depth Visual Introduction For Beginners

    2017 · amazon.com · its alternatives →

17. 17
    Minimal LLM Post-Training Experiments on an 8GB GPU (SFT, DPO, GRPO)▲21

    Minimal, readable LLM post-training experiments on one 8GB GPU. Measures forgetting, seed variance, and RL emergence. - pochenai/nano-llm-posttraining

    Aug 2026 · github.com · its alternatives →

18. 18PA
    Philip2 – an Elm-to-OCaml compiler▲8

    2019 · medium.com · its alternatives →

19. 19
    Poodle, Python-to-PDDL Compiler and AI Planning SDK▲9

    2019 · github.com · its alternatives →

20. 20
    Environment Builder for Robot/RL (Full Layer L1"MeshWi-Fi" to L7"K8s")▲6

    2019 · github.com · its alternatives →

21. 21
    BlockDL▲12

    Hi everyone. Designing neural network architectures is inherently a visual process. Every time I train a new model, I find myself sketching it out on paper before translating it into code (and still running into shape mismatches no matter how many networks I've built). So I built BlockDL: a free and open-source tool to design neural networks visually in your browser. It updates live Python/Keras code as you build, and automatically checks for shape and connectivity errors in real time. It supports: - Most common layer types (Conv2D, Dense, LSTM, etc.) - Multiple input/output…

    2025 · blockdl.com · its alternatives →

22. 22TL
    Tengo lang – A fast script language for Go▲6

    2019 · tengolang.com · its alternatives →

23. 23
    KANN – mid-scale deep learning and autodiff in ANSI C (4 files; 4k LOC)▲5

    A lightweight C library for artificial neural networks - attractivechaos/kann

    2018 · github.com · its alternatives →

24. 24
    Open-source implementation of Meta's Unit TestGen–LLM in Golang▲5

    2024 · github.com · its alternatives →

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 →