AI · alternatives · 2026

Inside a Neural Network is a tutorial that teaches users how to build a basic feedforward neural network with backpropagation in Python. Designed for people new to machine learning, it requires familiarity with basic… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Inside a Neural Network launched in 2018; newer entries below may have overtaken it.

1. 1
   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 →

2. 2AV
   A Visual and Interactive Guide to the Basics of Neural Networks▲63

   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 →

3. 3
   I built a game to help you learn neural network architectures▲321

   2024 · graphgame.sabrina.dev · its alternatives →

4. 4
   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 →

5. 5
   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 →

6. 6AI
   An Interactive Guide to Teach Derivatives and Backpropagation▲119

   2023 · x0axz.com · its alternatives →

7. 7
   I built a deep learning engine from scratch in Python▲30

   I’ve spent the last few months building a deep learning engine completely from scratch in Python (using only math and random). What started as a basic linear algebra calculator project grew into a symbolic tensor system with autodiff, custom matrix ops, attention mechanisms, LayerNorm, GELU, and even a text generation demo trained on the Brown corpus. I'm still an undergrad, so my main goal is to deeply understand how deep learning actually works under the hood - gradients, attention, backpropagation, optimizers - by building it step-by-step with full visibility into everything, and without…

   2025 · github.com · its alternatives →

8. 8
   MakeML▲274

   Train Neural Networks without a line of code

   2019 · makeml.app · its alternatives →

9. 9IM
   I made a 5 hour neural networks class with no prerequisites▲17

   2017 · neuralnetsforhackers.teachable.com · its alternatives →

10. 10AB
    A browser-based neural network simulation▲31

    2015 · neurovis.dataphoric.com · its alternatives →

11. 11
    Python Machine Learning – A Crash Course▲350

    :speech_balloon: Machine Learning Course with Python: - GitHub - instillai/machine-learning-course: :speech_balloon: Machine Learning Course with Python:

    2019 · github.com · its alternatives →

12. 12
    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 →

13. 13
    Visualizing a neural network as it learns▲9

    An interactive neural network with backpropagation that learns logical operators like XOR, OR, NAND, and AND in real time.

    2014 · emergentmind.com · its alternatives →

14. 14
    LambdaNet – A functional neural network library written in Haskell▲56

    Purely functional artificial neural network library implemented in Haskell. - jbarrow/LambdaNet

    2014 · github.com · its alternatives →

15. 15
    Natural Language Processing Demystified (Part One)▲166

    Hi HN: I published part one of my free NLP course. The course is intended to help anyone who knows Python and a bit of math go from the very basics all the way to today's mainstream models and frameworks. I strive to balance theory and practice and so every module consists of detailed explanations and slides along with a Colab notebook (in most modules) putting the theory into practice. In part one, we cover text preprocessing, how to turn text into numbers, and multiple ways to classify and search text using "classical" approaches. And along the way, we'll pick up useful bits on how to use…

    2022 · nlpdemystified.org · its alternatives →

16. 16
    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 →

17. 17
    I trained a neural network to write Kanji▲166

    sketch-rnn model trained to write kanji.

    2018 · otoro.net · its alternatives →

18. 18
    I trained a neural network to learn Arabic morphology▲183

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

    2018 · github.com · its alternatives →

19. 19AL
    A little notebook for learning linear algebra with Python▲190

    2025 · little-book-of.github.io · its alternatives →

20. 20
    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 →

21. 21
    Simple Neural Network▲7

    Simple way to learn neural network on C++

    2023 · github.com · its alternatives →

22. 22
    Neural Network Tutorial▲3

    Intuitive, natural, cohesive tutorial for neural networks

    2024 · leapai.top · its alternatives →

23. 23
    How to Create Image Recognition▲3

    Tutorial - How to Create Image Recognition With Python

    2020 · blog.duomly.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 →

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 →