Gradient

just a simple gradient tool

growingnn is a cutting-edge Python package that introduces a dynamic neural network architecture learning algorithm. This innovative approach allows the neural network to adapt its structure during training, optimizing both weights and architecture. Leveraging a Stochastic Gradient Descent-based optimizer and guided Monte Carlo tree search, the package provides a powerful tool for enhancing model performance. Now with PyTorch support for enhanced performance and GPU acceleration!

Influence Estimation for Gradient-Boosted Decision Trees

A package compatible with scikit-learn.

High throughput asynchronous reinforcement learning framework

llama-index llms gradient integration

CLI for printing text in gradient color using the rich-gradient library.

A plug-and-use python library to monitor learning of PyTorch neural networks

Method PROTES (PRobabilistic Optimizer with TEnsor Sampling) for derivative-free optimization of the multidimensional arrays and discretized multivariate functions based on the tensor train (TT) format

Field and gradient calculations for magnetic coils

Python Image Displacement Identification.

Instance-Based Uncertainty Estimation for Gradient-Boosted Regression Trees

PyTorch optimizer based on nonlinear conjugate gradient method

feature and feature interaction analyzer for gradient boosting

Calculations

A Python package for determining the structures of materials with gradient-based methods.

A Python package for gradient colors

Neural Network Gradient Metrics with PyTorch

A library which Predicts the Y value(output) for given test data points using gradient descend algorithm.

Gradient descent implementation for ML

GPU memory-efficient training with gradient compression for PyTorch

Makes learning gradient descent easy

A CLI for maxludden/maxgradient

API of gradient descent.

Ingradient - A labeling and dataset management tool

Hybrid time series forecasting library combining Prophet with gradient boosting models

BIRT is an implementation of Beta3-irt using gradient descent.

Complete Python SDK for DigitalOcean's Gradient AI Platform - serverless inference, knowledge bases, agents, and more

CEEMDAN-LSTM-GradientBoosting model for state-of-the-art time series forecasting

Gradient Boosting libraries integrated with PyTorch

A python package containing implementations of two widely used algorithms to minimise any function - Gradient Descent algorithm and the Normal Equation method.

Sionna - A hardware-accelerated differentiable open-source library for research on communication systems

Learning Environment for Agent Reasoning Networks — Unified framework for specifying, composing, optimizing, and evaluating LLM-based systems

Advanced numerical function interpolation and differentiation with universal API, multivariate calculus, window functions, and stochastic extensions

Signal-Adaptive Residual Boosting — two-phase gradient boosting with per-tree OOB step optimization

Gradient Boosting and Probabilistic Regression with categorical structure

SVG Frame-by-Frame Animation Generator - Create optimized FBF SVG animations from SVG sequences

CSS gradient generator

Where you find all the state-of-the-art cooking utensils (salt, pepper, gradient descent... the usual).

An implementation of Mesh Adaptive Direct Search (MADS) for gradient-free optimization.

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

Sobel Gradient Image Deduplication

Fully automated LC gradient optimization of optimal compound separation in nontargeted metabolomics

Medical Deep Learning Framework

A flet component for gradient borders

A package for applying differential privacy to model training using gradient shuffling and membership inference attack detection.

A small machine learning library for doing gradient boosting

A modular approach to topology optimization

AI governance layer. Local-first. Open source. Three layers: hard constraints, gradient decisions, self-audit.