Gradient Descent Python Packages

neural-tangents

Fast and Easy Infinite Neural Networks in Python

networks

Library which can be used to build feed forward NN, Convolutional Nets, Linear Regression, and Logistic Regression Models.

torchzero

Modular optimization library for PyTorch (work-in-progress).

descent

First-order optimization tools

ml-python

Easy to use high level python library for popular machine learning algorithms. Has in-built support for graphing and optimizers based in C++.

rose-opt

🌹 Rose: Range-Of-Slice Equilibration PyTorch optimizer. Stateless optimization through range-normalized gradient updates.

torchimize

numerical optimization in pytorch

grande

(ICLR 2024) GRANDE: Gradient-Based Decision Tree Ensembles

spsa

A simple implementation of SPSA with automatic learning rate tuning

mlektic

A Python ML library to use and visualize gradient descent for linear and logistic regression optimization.

nets

Recreating PyTorch from scratch, using Numpy. Supports FCN, CNN, RNN layers.

yodf

'Hello, World!' Forward Mode Autdiff library with Tensorflow 1 like interface.

torch-cgd

A fast implementation of adaptive competitive gradient descent in PyTorch 🤺

mlr-gd

A package for multiple linear regression by gradient descent.

simpliml

Machine Learning, Artificial Intelligence, Mathematics

dlfs

implement from scratch (using numpy arrays) a package based on tensorflow architecture which allows to build and train Fully Connected Networks and Convolutional Neural Networks (CNNs).

fastcpd

Fast Change Point Detection in R

gradient-equilibrum

An implementation of an Gradient Algorithm that fines the equilibrium instead of the minimum or maximum

tno-mpc-mpyc-secure-learning

TNO PET Lab - secure Multi-Party Computation (MPC) - MPyC - Secure Learning

waveletml

WaveletML: A Scalable and Extensible Wavelet Neural Network Framework

psd-optimizer

Perturbed Saddle-escape Descent (PSD): a first-order optimizer that escapes strict saddle points in nonconvex problems.

optimisation-algorithms

A collection of the most commonly used Optimisation Algorithms for Data Science & Machine Learning

findi-descent

FinDi: Finite Difference Gradient Descent can optimize any function, including the ones without analytic form, by employing finite difference numerical differentiation within a gradient descent algorithm.

cbar

A Python package for content-based audio retrieval with text queries.