Gradient Descent
Showing 15 of 15 projects
A fast online machine learning system with advanced techniques like hashing, reductions, and contextual bandits.
A comprehensive guide to TensorFlow 2.x covering fundamentals, best practices, and advanced topics for efficient machine learning development.
A library for building and evaluating mathematical expressions and neural networks in Go, with automatic differentiation and GPU support.
A high-level neural network API for specifying and analyzing infinite-width neural networks as Gaussian Processes in Python.
A modular neural network package for Torch providing building blocks for creating and training deep learning models.
A pure Rust numerical optimization library offering a wide range of algorithms with a consistent, type-agnostic interface.
A Common Lisp machine learning library focusing on neural networks, Boltzmann machines, and Gaussian processes with BLAS and CUDA support.
A JAX library for nonlinear optimization including root finding, minimization, fixed points, and least squares.
A collection of optimization algorithms and logging utilities for Torch machine learning models.
A Python package providing gradient-based optimizers specifically designed for machine learning scenarios.
A Haskell library for building and training feed-forward neural networks with automatic differentiation.
Bayesian inference tools in Python for estimating Dirichlet priors and multinomial mixture models from discrete event data.
A Swift library for accelerated tensor operations and dynamic neural networks with automatic differentiation, supporting all Apple platforms and Linux.
A Node.js library for machine learning with linear regression and k-means clustering algorithms.
An experimental extension to Torch7's nn package, providing unproven neural network modules and optimizations.
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