BayesianoptimizationA Python implementation of global optimization with gaussian processes.
Stars: ✭ 5,611 (+4025.74%)
Bayesian OptimizationPython code for bayesian optimization using Gaussian processes
Stars: ✭ 245 (+80.15%)
Cornell MoeA Python library for the state-of-the-art Bayesian optimization algorithms, with the core implemented in C++.
Stars: ✭ 198 (+45.59%)
ultraoptDistributed Asynchronous Hyperparameter Optimization better than HyperOpt. 比HyperOpt更强的分布式异步超参优化库。
Stars: ✭ 93 (-31.62%)
Quantum LearningThis repository contains the source code used to produce the results presented in the paper "Machine learning method for state preparation and gate synthesis on photonic quantum computers".
Stars: ✭ 89 (-34.56%)
Training MaterialA collection of code examples as well as presentations for training purposes
Stars: ✭ 85 (-37.5%)
Far HoGradient based hyperparameter optimization & meta-learning package for TensorFlow
Stars: ✭ 161 (+18.38%)
IminuitJupyter-friendly Python interface for C++ MINUIT2
Stars: ✭ 172 (+26.47%)
pyrffpyrff: Python implementation of random fourier feature approximations for gaussian processes
Stars: ✭ 24 (-82.35%)
approxposteriorA Python package for approximate Bayesian inference and optimization using Gaussian processes
Stars: ✭ 36 (-73.53%)
Hyperopt.jlHyperparameter optimization in Julia.
Stars: ✭ 144 (+5.88%)
Deeplearning.ai NotesThese 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.
Stars: ✭ 262 (+92.65%)
Optimization PythonGeneral optimization (LP, MIP, QP, continuous and discrete optimization etc.) using Python
Stars: ✭ 133 (-2.21%)
Neural TangentsFast and Easy Infinite Neural Networks in Python
Stars: ✭ 1,357 (+897.79%)
LimboA lightweight framework for Gaussian processes and Bayesian optimization of black-box functions (C++-11)
Stars: ✭ 157 (+15.44%)
Fantasy Basketball Scraping statistics, predicting NBA player performance with neural networks and boosting algorithms, and optimising lineups for Draft Kings with genetic algorithm. Capstone Project for Machine Learning Engineer Nanodegree by Udacity.
Stars: ✭ 146 (+7.35%)
Quant NotesQuantitative Interview Preparation Guide, updated version here ==>
Stars: ✭ 180 (+32.35%)
AutoOEDAutoOED: Automated Optimal Experimental Design Platform
Stars: ✭ 87 (-36.03%)
Gradient Free OptimizersSimple and reliable optimization with local, global, population-based and sequential techniques in numerical discrete search spaces.
Stars: ✭ 711 (+422.79%)
SimpleExperimental Global Optimization Algorithm
Stars: ✭ 450 (+230.88%)
Ts EmoThis repository contains the source code for “Thompson sampling efficient multiobjective optimization” (TSEMO).
Stars: ✭ 39 (-71.32%)
AthenaAutomatic equation building and curve fitting. Runs on Tensorflow. Built for academia and research.
Stars: ✭ 57 (-58.09%)
hyper-enginePython library for Bayesian hyper-parameters optimization
Stars: ✭ 80 (-41.18%)
MlrmboToolbox for Bayesian Optimization and Model-Based Optimization in R
Stars: ✭ 173 (+27.21%)
SafeoptSafe Bayesian Optimization
Stars: ✭ 90 (-33.82%)
AdvisorOpen-source implementation of Google Vizier for hyper parameters tuning
Stars: ✭ 1,359 (+899.26%)
YaboxYet another black-box optimization library for Python
Stars: ✭ 103 (-24.26%)
GPimGaussian processes and Bayesian optimization for images and hyperspectral data
Stars: ✭ 29 (-78.68%)
HyperactiveA hyperparameter optimization and data collection toolbox for convenient and fast prototyping of machine-learning models.
Stars: ✭ 182 (+33.82%)
ChocolateA fully decentralized hyperparameter optimization framework
Stars: ✭ 112 (-17.65%)
Scikit OptimizeSequential model-based optimization with a `scipy.optimize` interface
Stars: ✭ 2,258 (+1560.29%)
mangoParallel Hyperparameter Tuning in Python
Stars: ✭ 241 (+77.21%)
Hyperlearn50% faster, 50% less RAM Machine Learning. Numba rewritten Sklearn. SVD, NNMF, PCA, LinearReg, RidgeReg, Randomized, Truncated SVD/PCA, CSR Matrices all 50+% faster
Stars: ✭ 1,204 (+785.29%)
GpstuffGPstuff - Gaussian process models for Bayesian analysis
Stars: ✭ 106 (-22.06%)
NasbotNeural Architecture Search with Bayesian Optimisation and Optimal Transport
Stars: ✭ 120 (-11.76%)
Keras Yolo2Easy training on custom dataset. Various backends (MobileNet and SqueezeNet) supported. A YOLO demo to detect raccoon run entirely in brower is accessible at https://git.io/vF7vI (not on Windows).
Stars: ✭ 1,693 (+1144.85%)
Pytorch 101 Tutorial SeriesPyTorch 101 series covering everything from the basic building blocks all the way to building custom architectures.
Stars: ✭ 136 (+0%)
Deeplearning.aideeplearning.ai , By Andrew Ng, All slide and notebook + code and some material.
Stars: ✭ 1,663 (+1122.79%)
FourierAn Interactive Introduction to Fourier Transforms
Stars: ✭ 1,809 (+1230.15%)
PytorchvizA small package to create visualizations of PyTorch execution graphs
Stars: ✭ 2,054 (+1410.29%)
Robust representationsCode for "Learning Perceptually-Aligned Representations via Adversarial Robustness"
Stars: ✭ 137 (+0.74%)
VentilatorLow-Cost Open Source Ventilator or PAPR
Stars: ✭ 1,665 (+1124.26%)
RiptideSimple Training and Deployment of Fast End-to-End Binary Networks
Stars: ✭ 135 (-0.74%)
Pycon Ds 2018Introduction to Python for Data Science for PyCon 2018
Stars: ✭ 135 (-0.74%)
DeeplearningfornlpinpytorchAn IPython Notebook tutorial on deep learning for natural language processing, including structure prediction.
Stars: ✭ 1,744 (+1182.35%)
Kyle School쏘카 데이터 그룹 사내 신입/인턴을 대상으로 한 카일 스쿨
Stars: ✭ 136 (+0%)
Part bilinear reidCode for ECCV2018 paper: Part-Aligned Bilinear Representations for Person Re-Identification
Stars: ✭ 135 (-0.74%)
Beyond Jupyter🐍💻📊 All material from the PyCon.DE 2018 Talk "Beyond Jupyter Notebooks - Building your own data science platform with Python & Docker" (incl. Slides, Video, Udemy MOOC & other References)
Stars: ✭ 135 (-0.74%)
Monthly ChallengesRepository containing monthly challenges about quantum computing.
Stars: ✭ 126 (-7.35%)