Welcome to nimblenet’s documentation!

nimblenet is a lightweight and efficient Numpy library for creating feed forward neural networks. The library was developed with PYPY in mind and should play nicely with their super-fast JIT compiler. The networks can be trained by a variety of learning algorithms: backpropagation, resilient backpropagation, adaptive learning rate backpropagation, scaled conjugate gradient and SciPy’s optimize function.

This is a list of handy links to get up and running.


$ pip install nimblenet


  • Python 2.7
  • NumPy
  • SciPy (optional). This is of course a required depedency if you intend to train the network using SciPy’s optimize function.


Have you spotted a bug, or run into inconsistencies in the documentation? Please report the issue at Github.