AI · alternatives · 2026

A Visual and Interactive Guide to the Basics of Neural Networks is an educational resource that explains machine learning concepts through interactive visualizations. Created by a software engineer new to AI, it breaks… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. A Visual and Interactive Guide to the Basics of Neural Networks launched in 2016; newer entries below may have overtaken it.

1. 1
   I built a game to help you learn neural network architectures▲321

   2024 · graphgame.sabrina.dev · its alternatives →

2. 2
   Neural networks tutorial series with code▲107

   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 →

3. 3AI
   An Interactive Guide to Teach Derivatives and Backpropagation▲119

   2023 · x0axz.com · its alternatives →

4. 4
   Comgra: A library for debugging and understanding neural networks▲66

   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 →

5. 5
   Simple and comprehensive tutorials in Deep Learning using TensorFlow▲157

   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. 6
   Comprehensive Tutorials in Deep Learning Using TensorFlow▲327

   :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 →

7. 7
   MLGarden, a tool/toy to build and train simple neural networks visually▲11

   I made this tool to get some better intuition on how neural networks/backpropagation worked, but I'm really unsure what to do with it now, so I've put it up on github, and I wrote a little primer on backprop and neural networks to showcase it. Really curious to hear any thoughts you might have, or anything I got wrong in the write up!

   2024 · github.com · its alternatives →

8. 8AB
   A browser-based neural network simulation▲31

   2015 · neurovis.dataphoric.com · its alternatives →

9. 9IA
   Inside a Neural Network▲13

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

   2018 · enlight.nyc · its alternatives →

10. 10
    I'm 15 and built a neural network from scratch in C++,just math▲8

    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. 11ID
    Interactive deep convnet visualization for Keras and Tensorflow▲124

    2016 · jakebian.github.io · its alternatives →

12. 12
    Neural Network Tutorial▲3

    Intuitive, natural, cohesive tutorial for neural networks

    2024 · leapai.top · its alternatives →

13. 13DL
    Deep Learning GUI to Create, Train and Visualize Models in a Browser▲216

    2019 · beta.aifiddle.io · its alternatives →

14. 14
    Single neuron neural network written in COBOL▲94

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

    2020 · github.com · its alternatives →

15. 15
    TensorSpace.js – Neural network 3D visualization framework▲167

    Neural network 3D visualization framework, build interactive and intuitive model in browsers, support pre-trained deep learning models from TensorFlow, Keras, TensorFlow.js - GitHub - tensorspace-team/tensorspace: Neural network 3D visualization framework, build interactive and intuitive model in br

    2018 · github.com · its alternatives →

16. 16GC
    Graph Convolutional Networks – Intro to neural networks on graphs▲106

    Many important real-world datasets come in the form of graphs or networks: social networks, knowledge graphs, protein-interaction networks, the World Wide Web, etc. (just to name a few). Yet, until recently, very little attention has been devoted to the generalization of neural...

    2016 · tkipf.github.io · its alternatives →

17. 17
    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 →

18. 18
    WhatTheFIsML▲110

    An illustrated guide to understanding Machine Learning

    2016 · its alternatives →

19. 19IT
    Intro to Machine Learning in Interactive D3.js Visualizations▲128

    Experiments in expressing statistical thinking with interactive design

    2015 · r2d3.us · its alternatives →

20. 20
    Machine Learning▲77

    A visual guide for beginners

    2017 · amazon.com · its alternatives →

21. 21
    Simple Deep Learning Tutorials using Microsoft Cognitive Toolkit▲126

    :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 →

22. 22
    Neural Networks and Deep Learning▲95

    Core concepts behind neural networks and deep learning

    2015 · neuralnetworksanddeeplearning.com · its alternatives →

23. 23IM
    I made a 5 hour neural networks class with no prerequisites▲17

    2017 · neuralnetsforhackers.teachable.com · its alternatives →

24. 24
    To better understand Neural Networks I built one from scratch in C++▲10

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

    2017 · github.com · its alternatives →

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