scikit-hep/iminuit

Non-Linear Least Squares Minimization, with flexible Parameter settings, based on scipy.optimize, and with many additional classes and methods for curve fitting.

Model manipulation and fitting library based on TensorFlow and optimised for simple and direct manipulation of probability density functions. Its main focus is on scalability, parallelisation and user friendly experience.

optimagic is a Python package for numerical optimization. It is a unified interface to optimizers from SciPy, NlOpt and other packages. optimagic's minimize function works just like SciPy's, so you don't have to adjust your code. You simply get more optimizers for free. On top you get diagnostic tools, parallel numerical derivatives and more.

pure-Python HistFactory implementation with tensors and autodiff

Fit models to your data in Python with Sherpa.

constrained nonlinear optimization for scientific machine learning, UQ, and AI

Fit and compare complex models reliably and rapidly. Advanced nested sampling.

Python implementation of CMA-ES

SciPy library main repository