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Search results for machine learning optimization
machine-learning
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optimization
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305 search results found
Ray
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29,596
Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Deep Learning Drizzle
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10,767
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
Serve
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3,844
Serve, optimize and scale PyTorch models in production
Scikit Optimize
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2,700
Sequential model-based optimization with a `scipy.optimize` interface
Awesome System For Machine Learning
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2,244
A curated list of research in machine learning systems (MLSys). Paper notes are also provided.
Awesome Quantum Machine Learning
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2,206
Here you can get all the Quantum Machine learning Basics, Algorithms ,Study Materials ,Projects and the descriptions of the projects around the web
Pennylane
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2,164
PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Train a quantum computer the same way as a neural network.
Awesome Robotics Libraries
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1,953
😎 A curated list of robotics libraries and software
Geneticalgorithmpython
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1,564
Source code of PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch).
Osqp
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1,540
The Operator Splitting QP Solver
Awesome Federated Learning
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1,481
FedML - The Research and Production Integrated Federated Learning Library: https://fedml.ai
Model Optimization
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1,445
A toolkit to optimize ML models for deployment for Keras and TensorFlow, including quantization and pruning.
Optax
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1,431
Optax is a gradient processing and optimization library for JAX.
Mlbox
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1,403
MLBox is a powerful Automated Machine Learning python library.
Hyperlearn
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1,387
2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.
Modelingtoolkit.jl
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1,292
An acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automated transformations of differential equations
Beautifulalgorithms.jl
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1,281
Concise and beautiful algorithms written in Julia
Awesome Machine Learning In Compilers
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1,239
Must read research papers and links to tools and datasets that are related to using machine learning for compilers and systems optimisation
Advisor
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1,202
Open-source implementation of Google Vizier for hyper parameters tuning
Owl
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1,178
Owl - OCaml Scientific Computing @ https://ocaml.xyz
Pyswarms
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1,154
A research toolkit for particle swarm optimization in Python
Vizier
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1,142
Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.
Gradient Free Optimizers
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1,072
Simple and reliable optimization with local, global, population-based and sequential techniques in numerical discrete search spaces.
Hyperparameter Optimization Of Machine Learning Algorithms
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1,025
Implementation of hyperparameter optimization/tuning methods for machine learning & deep learning models (easy&clear)
Generalization Causality
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993
关于domain generalization,domain adaptation,causality,robutness,prompt,optimization model各式各样研究的阅读笔记
Wheels
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885
Performance-optimized wheels for TensorFlow (SSE, AVX, FMA, XLA, MPI)
Tiramisu
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872
A polyhedral compiler for expressing fast and portable data parallel algorithms
Awesome Robotics
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817
A curated list of awesome links and software libraries that are useful for robots.
Jenetics
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806
Jenetics - Genetic Algorithm, Genetic Programming, Grammatical Evolution, Evolutionary Algorithm, and Multi-objective Optimization
Teaching
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802
Teaching Materials for Dr. Waleed A. Yousef
Deepdow
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790
Portfolio optimization with deep learning.
Spot_mini_mini
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783
Dynamics and Domain Randomized Gait Modulation with Bezier Curves for Sim-to-Real Legged Locomotion.
Eaopt
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721
🍀 Evolutionary optimization library for Go (genetic algorithm, partical swarm optimization, differential evolution)
Test Tube
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719
Python library to easily log experiments and parallelize hyperparameter search for neural networks
Evalml
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679
EvalML is an AutoML library written in python.
Ensmallen
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675
A header-only C++ library for numerical optimization --
Hyperparameter_hunter
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635
Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries
Qpth
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604
A fast and differentiable QP solver for PyTorch.
Ml Compiler Opt
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553
Infrastructure for Machine Learning Guided Optimization (MLGO) in LLVM.
Neptune Client
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518
📘 The MLOps stack component for experiment tracking
Solid
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518
🎯 A comprehensive gradient-free optimization framework written in Python
Hyperactive
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475
An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.
Tick
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453
Module for statistical learning, with a particular emphasis on time-dependent modelling
Ojalgo
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448
oj! Algorithms
Mica
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409
MICA - Towards Metrical Reconstruction of Human Faces [ECCV2022]
Zoopt
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360
A python package of Zeroth-Order Optimization (ZOOpt)
Automlpipeline.jl
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331
A package that makes it trivial to create and evaluate machine learning pipeline architectures.
Optnet
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321
OptNet: Differentiable Optimization as a Layer in Neural Networks
Sherpa
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294
Hyperparameter optimization that enables researchers to experiment, visualize, and scale quickly.
Sigpy
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276
Python package for signal processing, with emphasis on iterative methods
Deeplearning.ai Notes
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271
These are my notes which I prepared during deep learning specialization taught by AI guru Andrew NG. I have used diagrams and code snippets from the code whenever needed but following The Honor Code.
Libauc
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262
LibAUC: A Deep Learning Library for X-Risk Optimization
Ecole
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259
Extensible Combinatorial Optimization Learning Environments
Componentarrays.jl
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258
Arrays with arbitrarily nested named components.
Maze
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249
Maze Applied Reinforcement Learning Framework
Functional_intro_to_python
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239
[tutorial]A functional, Data Science focused introduction to Python
Kernel_tuner
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236
Kernel Tuner
Pygpgo
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236
Bayesian optimization for Python
Deeplearningwithtf2.0
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227
Practical Exercises in TensorFlow 2.0 for Ian Goodfellows Deep Learning Book
Gpflowopt
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218
Bayesian Optimization using GPflow
Learningx
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213
Deep & Classical Reinforcement Learning + Machine Learning Examples in Python
Zoofs
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213
zoofs is a python library for performing feature selection using a variety of nature-inspired wrapper algorithms. The algorithms range from swarm-intelligence to physics-based to Evolutionary. It's easy to use , flexible and powerful tool to reduce your feature size.
Autogoal
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203
A Python framework for program synthesis with a focus on Automated Machine Learning.
Auptimizer
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195
An automatic ML model optimization tool.
Benchopt
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193
Making your benchmark of optimization algorithms simple and open
Nips_2017
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185
videos, slides, and others from NIPS 2017
Deep Learning Dynamics Paper List
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183
This is a list of peer-reviewed representative papers on deep learning dynamics (optimization dynamics of neural networks). The success of deep learning attributes to both network architecture and stochastic optimization. Thus, deep learning dynamics play an essentially important role in theoretical foundation of deep learning.
Sgdlibrary
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181
MATLAB/Octave library for stochastic optimization algorithms: Version 1.0.20
Kfac Jax
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178
Second Order Optimization and Curvature Estimation with K-FAC in JAX.
Ml Systems
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175
papers on scalable and efficient machine learning systems
L4casadi
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175
Use PyTorch Models with CasADi and Acados in Python, C(++) or Matlab
Go Tsne
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169
t-Distributed Stochastic Neighbor Embedding (t-SNE) in Go
Cornell Moe
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165
A Python library for the state-of-the-art Bayesian optimization algorithms, with the core implemented in C++.
K Means Constrained
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164
K-Means clustering - constrained with minimum and maximum cluster size. Documentation: https://joshlk.github.io/k-means-constrained
Adcme.jl
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158
Automatic Differentiation Library for Computational and Mathematical Engineering
Quantum Neural Networks
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156
This repository contains the source code used to produce the results presented in the paper "Continuous-variable quantum neural networks". Due to subsequent interface upgrades, these scripts will work only with Strawberry Fields version <= 0.10.0.
Channelbreakoutbot
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151
Channel Breakout Bot for bitflyer-FX
Adatune
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144
Gradient based Hyperparameter Tuning library in PyTorch
Gravity
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143
Mathematical Modeling for Optimization and Machine Learning
Hype
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139
Hype: Compositional Machine Learning and Hyperparameter Optimization
Pyxab
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135
PyXAB - A Python Library for X-Armed Bandit and Online Blackbox Optimization Algorithms
E2e Model Learning
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133
Task-based end-to-end model learning in stochastic optimization
Monet
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131
MONeT framework for reducing memory consumption of DNN training
Learn To Select Data
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131
Code for Learning to select data for transfer learning with Bayesian Optimization
Mlogger
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127
a lightweight and simple logger for Machine Learning
Copt
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122
A Python library for mathematical optimization
Raytracer.jl
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121
Differentiable RayTracing in Julia
Ycml
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118
A Machine Learning and Optimization framework for Objective-C and Swift (MacOS and iOS)
Miplearn
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117
Framework for solving discrete optimization problems using a combination of Mixed-Integer Linear Programming (MIP) and Machine Learning (ML)
Baybe
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117
A Bayesian Back End for Design of Experiments
Proximalalgorithms.jl
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117
Proximal algorithms for nonsmooth optimization in Julia
Limes
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114
Link Discovery Framework for Metric Spaces.
Mu8
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110
Genetic algorithm for unsupervised machine learning in Go.
Xitorch
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108
Differentiable scientific computing library
Mlsl
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107
Intel(R) Machine Learning Scaling Library is a library providing an efficient implementation of communication patterns used in deep learning.
Qmlt
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102
The Quantum Machine Learning Toolbox (QMLT) is a Strawberry Fields application that simplifies the optimization of variational quantum circuits (also known as parametrized quantum circuits).
Quant Notes
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101
Quantitative Interview Preparation Guide, updated version here ==>
Stackexchangecodes
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100
Codes related to answers on StackExchange Network.
Adaptive Inertia Adai
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94
The PyTorch Implementation of Adaptive Inertia Methods. The algorithms are based on our ICML2022 Oral paper: "Adaptive Inertia: Disentangling the Effects of Adaptive Learning Rate and Momentum".
30 Days Of Ml Kaggle
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93
Machine learning beginner to Kaggle competitor in 30 days. Non-coders welcome. The program starts Monday, August 2, and lasts four weeks. It's designed for people who want to learn machine learning.
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