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29 search results found

Captainblackboard ⭐ 1,047

船长关于机器学习、计算机视觉和工程技术的总结和分享

Awesome Robotics ⭐ 817

A curated list of awesome links and software libraries that are useful for robots.

Ensmallen ⭐ 675

A header-only C++ library for numerical optimization --

Dist Keras ⭐ 611

Distributed Deep Learning, with a focus on distributed training, using Keras and Apache Spark.

L4casadi ⭐ 175

Use PyTorch Models with CasADi and Acados in Python, C(++) or Matlab

Deeplearning.ai ⭐ 110

Viz_torch_optim ⭐ 96

Videos of deep learning optimizers moving on 3D problem-landscapes

Psgd_torch ⭐ 86

Pytorch implementation of preconditioned stochastic gradient descent (affine group preconditioner, low-rank approximation preconditioner and more)

Jestimator ⭐ 77

Amos optimizer with JEstimator lib.

Hyper Engine ⭐ 69

Python library for Bayesian hyper-parameters optimization

Machine Learning In Python Workshop ⭐ 54

My workshop on machine learning using python language to implement different algorithms

Neural Net Optimization ⭐ 49

PyTorch implementations of recent optimization algorithms for deep learning.

Littleconv ⭐ 45

The C++11 deep learning framework, which is very easy to use

Keras-like APIs for JAX framework

Deep Learning Optimization Algorithms ⭐ 37

Visualization of various deep learning optimization algorithms using PyTorch automatic differentiation and optimizers.

Tensorflow implementation of preconditioned stochastic gradient descent

Learning Lab C Library ⭐ 30

This library provides a set of basic functions for different type of deep learning (and other) algorithms in C.This deep learning library will be constantly updated

Variance_reduced_neural_networks ⭐ 29

Implementation of SVRG and SAGA optimization algorithms for deep learning topics.

Csmath 2021 ⭐ 26

This mathematics course is taught for the first year Ph.D. students of computer science and related areas @zju

Photonics Fdtd Drl ⭐ 14

Optimization and inverse design of photonic crystals using deep reinforcement learning

Chameleonquant ⭐ 11

chameleonQuant was born as an open-source Java framework to help enthusiast quants to implement system trading strategies and dynamic portfolio trading systems using advanced optimization techniques, machine learning, and deep learning techniques.

Intro_to_dl_tutorial ⭐ 11

Material for introduction to Deep Learning Tutorials, Summer '20, '21

AdaShift optimizer implementation in PyTorch

Optimization In Deep Learning ⭐ 8

Optimization algorithms commonly used in deep learning, mini-batch GD, SGD, and momentum methods AdapGrad, Adam... advanced methods Newton, quasi-Newton, L-BFGS...

Eeg Emotion Recognition ⭐ 7

EEG-Based Emotion Recognition

Pytorchhessianfree ⭐ 6

PyTorch implementation of the Hessian-free optimizer

Simple Evolutionary Feature Search ⭐ 6

evolutionary feature algorithm for finding features in the models

A simple and extensible image recognition neural network framework

ND-Adam is a tailored version of Adam for training DNNs.

Deep Learning ⭐ 5

Random Bases ⭐ 5

Improving Neural Network Training in Low Dimensional Random Bases

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