Gradient Descent Python Packages

neural-tangents

Fast and Easy Infinite Neural Networks in Python

rose-opt

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

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).

grande

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

torchimize

numerical optimization in pytorch

spsa

A simple implementation of SPSA with automatic learning rate tuning

ml-python

The easiest way to do machine learning

nets

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

descent

First-order optimization tools

mlektic

A simple machine learning python library.

torch-cgd

A fast implementation of adaptive competitive gradient descent in PyTorch 🤺

yodf

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

simpliml

SimpliML is a versatile machine learning library designed to be a one-stop solution for the entire data lifecycle. Whether you're preparing raw data or deploying advanced predictive models, SimpliML simplifies every step of the machine learning process

mlr-gd

Multiple linear regression by gradient descent.

fastcpd

Fast Change Point Detection in R

dlfs

Implementation from scratch (using numpy arrays) of a framework based on keras interface which allows to build and train Fully Connected Networks and Convolutional Neural Networks (CNNs).

tno-mpc-mpyc-secure-learning

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

gradient-equilibrum

Gradient Equillibrum - Pytorch

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.