FlexNN's a C++ neural net lib for dense layers, ReLU/Softmax, MNIST-focused. Arbitrary layers, but bare-bones POC.

How do you build neural networks from scratch in C++?

Code matrices, forward/backprop, activations manually. Use Eigen or raw arrays. Expect pain, gain backprop wisdom.

Does FlexNN replace TensorFlow?

Nope. Author says use TF. FlexNN's for learning, not production.

FlexNN: C++ Neural Nets from Scratch – Toy or Triumph?

Want flexible neural networks in C++? FlexNN promises it – barely. It's a learning stunt that exposes backprop's guts, but don't bet your startup on it.

theAIcatchup Apr 10, 2026 3 min read

FlexNN neural network diagram showing layers, weights, and MNIST digit recognition

⚡ Key Takeaways

FlexNN teaches backprop guts in pure C++, no frameworks. 𝕏
Limited to dense layers and basic activations – POC only. 𝕏
Stick to TensorFlow for real work; this is educational masochism. 𝕏

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#C# #FlexNN #MNIST #MNIST backprop #backpropagation #from scratch NN #neural networks #neural networks C++

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⚡ Key Takeaways

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