GitHub topics: hyperparameters

Repositories

rodrigo-arenas/Sklearn-genetic-opt

ML hyperparameters tuning and features selection, using evolutionary algorithms.

Language: Python - Size: 124 MB - Last synced at: 3 days ago - Pushed at: 3 days ago - Stars: 339 - Forks: 82

openmole/openmole

Workflow engine for exploration of simulation models using high throughput computing

Language: Scala - Size: 151 MB - Last synced at: 11 days ago - Pushed at: 11 days ago - Stars: 144 - Forks: 39

neptune-ai/neptune-optuna

🚀 Optuna visualization dashboard that lets you log and monitor hyperparameter sweep live.

Language: Python - Size: 179 KB - Last synced at: 12 days ago - Pushed at: 12 days ago - Stars: 12 - Forks: 5

openmole/mgo

Purely functional genetic algorithms for multi-objective optimisation

Language: Scala - Size: 3.48 MB - Last synced at: 12 days ago - Pushed at: 12 days ago - Stars: 72 - Forks: 5

tobegit3hub/advisor

Open-source implementation of Google Vizier for hyper parameters tuning

Language: Jupyter Notebook - Size: 3.41 MB - Last synced at: 10 days ago - Pushed at: over 5 years ago - Stars: 1,556 - Forks: 257

The world's cleanest AutoML library ✨ - Do hyperparameter tuning with the right pipeline abstractions to write clean deep learning production pipelines. Let your pipeline steps have hyperparameter spaces. Design steps in your pipeline like components. Compatible with Scikit-Learn, TensorFlow, and most other libraries, frameworks and MLOps environments.

Language: Python - Size: 8.16 MB - Last synced at: 16 days ago - Pushed at: about 1 month ago - Stars: 612 - Forks: 62

Techtonique/GPopt

Bayesian optimization using Gaussian Process regression (Python)

Language: HTML - Size: 7.07 MB - Last synced at: 1 day ago - Pushed at: 26 days ago - Stars: 3 - Forks: 0

araffin/rl-baselines-zoo 📦

A collection of 100+ pre-trained RL agents using Stable Baselines, training and hyperparameter optimization included.

Language: Python - Size: 367 MB - Last synced at: 23 days ago - Pushed at: over 2 years ago - Stars: 1,175 - Forks: 209

mduszyk/paramflow

A lightweight Python library for hyperparameter and configuration management

Language: Python - Size: 60.5 KB - Last synced at: 2 days ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0

RaduBolbo/video_to_panorama

video2panorama is a Python-based tool designed to transform video sequences into panoramic images. It automates the stitching process by analyzing frames from input video files and producing panoramic outputs.

Language: Python - Size: 29.9 MB - Last synced at: 27 days ago - Pushed at: about 2 months ago - Stars: 4 - Forks: 1

gyrdym/ml_algo

Machine learning algorithms in Dart programming language

Language: Dart - Size: 9.49 MB - Last synced at: 13 days ago - Pushed at: about 1 month ago - Stars: 192 - Forks: 31

KennethanCeyer/awesome-llm

Awesome series for Large Language Model(LLM)s

Size: 329 KB - Last synced at: about 1 month ago - Pushed at: 3 months ago - Stars: 80 - Forks: 5

FluxML/ParameterSchedulers.jl

Common hyperparameter scheduling for ML

Language: Julia - Size: 1.33 MB - Last synced at: 9 days ago - Pushed at: 6 months ago - Stars: 36 - Forks: 13

automl/DeepCAVE

An interactive framework to visualize and analyze your AutoML process in real-time.

Language: Python - Size: 58.3 MB - Last synced at: 6 days ago - Pushed at: 6 days ago - Stars: 87 - Forks: 13

ksachdeva/scikit-nni

AutoML - Hyper parameters search for scikit-learn pipelines using Microsoft NNI

Language: Python - Size: 11.7 MB - Last synced at: 20 days ago - Pushed at: over 2 years ago - Stars: 24 - Forks: 3

zygmuntz/hyperband

Tuning hyperparams fast with Hyperband

Language: Python - Size: 370 KB - Last synced at: 2 months ago - Pushed at: almost 7 years ago - Stars: 593 - Forks: 72

MLBazaar/MLBlocks

A library for composing end-to-end tunable machine learning pipelines.

Language: Python - Size: 7.81 MB - Last synced at: 11 days ago - Pushed at: 4 months ago - Stars: 116 - Forks: 35

andreacasalino/GaussianProcesses

Modern C++ library handling gaussian processes

Language: C++ - Size: 3.91 MB - Last synced at: about 2 months ago - Pushed at: over 2 years ago - Stars: 17 - Forks: 2

MaurizioFD/RecSys2019_DeepLearning_Evaluation

This is the repository of our article published in RecSys 2019 "Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches" and of several follow-up studies.

Language: Python - Size: 216 MB - Last synced at: 28 days ago - Pushed at: about 2 years ago - Stars: 987 - Forks: 249

MattKleinsmith/pbt

Population Based Training (in PyTorch with sqlite3). Status: Unsupported

Language: Python - Size: 120 KB - Last synced at: 3 months ago - Pushed at: over 7 years ago - Stars: 166 - Forks: 25

seba-1511/randopt

Streamlined machine learning experiment management.

Language: HTML - Size: 9.89 MB - Last synced at: 15 days ago - Pushed at: about 5 years ago - Stars: 107 - Forks: 8

mlr-org/paradox

ParamHelpers Next Generation

Language: R - Size: 11.3 MB - Last synced at: 14 days ago - Pushed at: 4 months ago - Stars: 29 - Forks: 7

MvMukesh/ProblemSolving-FrameWork-ML

Detailed industry specific framework to solve Machine Learning Problem

Language: Python - Size: 139 KB - Last synced at: 5 months ago - Pushed at: 5 months ago - Stars: 3 - Forks: 0

guybedo/minos

Deep learning, architecture and hyper parameters search with genetic algorithms

Language: Python - Size: 154 KB - Last synced at: about 2 months ago - Pushed at: 10 months ago - Stars: 52 - Forks: 10

Zen204/-my-ecornell-portfolio

Includes all of my Jupyter Notebook assignments from my time at MIT's Break Through AI/ML Program.

Language: Jupyter Notebook - Size: 9.24 MB - Last synced at: 2 months ago - Pushed at: 5 months ago - Stars: 0 - Forks: 0

devmunoz/avocado-price-predictor

Machine Learning Project

Language: Jupyter Notebook - Size: 5.72 MB - Last synced at: 2 months ago - Pushed at: 6 months ago - Stars: 0 - Forks: 0

PetrochukM/HParams

Configure Python functions explicitly and safely

Language: Python - Size: 210 KB - Last synced at: about 1 month ago - Pushed at: 7 months ago - Stars: 126 - Forks: 8

Minyus/optkeras 📦

OptKeras: wrapper around Keras and Optuna for hyperparameter optimization

Language: Python - Size: 37.2 MB - Last synced at: 15 days ago - Pushed at: about 5 years ago - Stars: 30 - Forks: 3

himkt/allennlp-optuna

⚡️ AllenNLP plugin for adding subcommands to use Optuna, making hyperparameter optimization easy

Language: Python - Size: 339 KB - Last synced at: 10 days ago - Pushed at: over 3 years ago - Stars: 33 - Forks: 5

eBay/AutoOpt

Automatic and Simultaneous Adjustment of Learning Rate and Momentum for Stochastic Gradient Descent

Language: Python - Size: 256 KB - Last synced at: about 1 month ago - Pushed at: almost 5 years ago - Stars: 45 - Forks: 12

priyadarshighosh/ANN_Everyday

Everything about Artificial Neural Network from Basic to Adavnced

Language: Jupyter Notebook - Size: 14.9 MB - Last synced at: 8 months ago - Pushed at: 8 months ago - Stars: 0 - Forks: 0

NicolasMICAUX/autohparams

Automatically create a config of hyper-parameters from global variables

Language: Python - Size: 74.2 KB - Last synced at: 17 days ago - Pushed at: 9 months ago - Stars: 1 - Forks: 0

aobeirne20/PytorchMNIST

Python GUI and PyTorch based backend to train a DNN or CNN on the MNIST handwriting dataset, classify digits the user draws in the GUI, and save hyperparameter info for a MATLAB graph.

Language: Python - Size: 49 MB - Last synced at: 10 months ago - Pushed at: over 3 years ago - Stars: 2 - Forks: 0

joydeepmedhi/Anchor-Boxes-with-KMeans

How to initialize Anchors in Faster RCNN for custom dataset?

Language: Jupyter Notebook - Size: 5.77 MB - Last synced at: about 1 month ago - Pushed at: almost 5 years ago - Stars: 91 - Forks: 31

zohaibterminator/machine-learning-specialization

Github repo for ML Specialization course on Coursera. Contains notes and practice python notebooks.

Language: Jupyter Notebook - Size: 21.3 MB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 0 - Forks: 0

Davityak03/Fashion-Mnist-Cnn-model-optimized-using-keras-tuner

Language: Jupyter Notebook - Size: 131 KB - Last synced at: 3 months ago - Pushed at: 11 months ago - Stars: 0 - Forks: 0

sdamadi/image-classification

Comprehensive image classification for training multilayer perceptron (MLP), LeNet, LeNet5, conv2, conv4, conv6, VGG11, VGG13, VGG16, VGG19 with batch normalization, ResNet18, ResNet34, ResNet50, MobilNetV2 on MNIST, CIFAR10, CIFAR100, and ImageNet1K.

Language: Python - Size: 46.1 MB - Last synced at: 2 months ago - Pushed at: over 3 years ago - Stars: 4 - Forks: 0

reiase/hyperparameter

Hyperparameter, Make configurable AI applications.Build for Python hackers.

Language: Rust - Size: 788 KB - Last synced at: 28 days ago - Pushed at: 12 months ago - Stars: 23 - Forks: 1

AnuragAnalog/Deep-Learning-Specialization

Coursera's Deep Learming Specialization Lecture notes

Language: Jupyter Notebook - Size: 310 MB - Last synced at: 19 days ago - Pushed at: almost 4 years ago - Stars: 2 - Forks: 1

isadays/DeepLearning

Deep Learning concepts and techniques: Regularization, Epochs, Batch,Hyperparameters, Cross validation, Optimizers

Language: Jupyter Notebook - Size: 79.1 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

PSTAT197-F23/Vignette-Random-Forests

Introduction and Implementation of Random Forest Models

Language: HTML - Size: 1.58 MB - Last synced at: about 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 1

davidenunes/params 📦

Simple parameter space creation library for python

Language: Python - Size: 23.4 KB - Last synced at: about 1 year ago - Pushed at: over 7 years ago - Stars: 0 - Forks: 0

atanasster/hyperparameters

ES6 hyperparameters search for tfjs

Language: JavaScript - Size: 90.8 KB - Last synced at: 11 days ago - Pushed at: over 4 years ago - Stars: 60 - Forks: 5

padas-lab-de/pypadre

In this research project, we aim to create an environment to gather structured data about machine learning experiments in order to analyze data and algorithmich dependencies.

Language: Python - Size: 7.26 MB - Last synced at: about 1 year ago - Pushed at: over 2 years ago - Stars: 3 - Forks: 1

Venu212/Optimizing-an-ML-Pipeline-in-Azure

build and optimize an Azure ML pipeline using the Python SDK and a provided Scikit-learn model. This model is then compared to a model from Azure AutoML

Language: Jupyter Notebook - Size: 2.05 MB - Last synced at: about 1 year ago - Pushed at: over 4 years ago - Stars: 0 - Forks: 0

C4ball/Udacity_Optimizing_a_Pipeline_in_Azure

This project is part of the Udacity Azure ML Nanodegree. In this project, we build and optimize an Azure ML pipeline using the Python SDK and a provided Scikit-learn model. This model is then compared to an Azure AutoML run.

Language: Jupyter Notebook - Size: 2.74 MB - Last synced at: over 1 year ago - Pushed at: over 4 years ago - Stars: 0 - Forks: 0

sumitkutty/AdvancedRegression-House-Prices

This project is a regression problem done as a part of the Kaggle competition.

Language: Jupyter Notebook - Size: 197 KB - Last synced at: over 1 year ago - Pushed at: over 4 years ago - Stars: 0 - Forks: 0

umutto/HyperparameterLogger

Simple logging wrapper for model hyperparameters from gensim.d2v, sklearn and keras.

Language: Python - Size: 13.7 KB - Last synced at: over 1 year ago - Pushed at: about 7 years ago - Stars: 0 - Forks: 0

chollette/Azure-Machine-Learning-Bank-Marketing-Classification

This is a Bank Marketing Machine Learning Classification Project in fulfillment of the Udacity Azure ML Nanodegree. In this project, you will learn to utilize Azure Machine Learning Studio and Azure Python SDK to create classifier models from scratch. The files and documentation with experiment instructions needed for replicating the project is provided for you.

Language: Jupyter Notebook - Size: 2.31 MB - Last synced at: over 1 year ago - Pushed at: over 4 years ago - Stars: 0 - Forks: 1

keplr-io/picard

Easily declare large spaces of (keras) neural networks and run (hyperopt) optimization experiments on them.

Language: Python - Size: 94.7 KB - Last synced at: 12 days ago - Pushed at: over 8 years ago - Stars: 52 - Forks: 5

eHarmony/spotz

Spark Parameter Optimization and Tuning

Language: Scala - Size: 227 KB - Last synced at: about 1 year ago - Pushed at: about 7 years ago - Stars: 31 - Forks: 8

ahirsharan/MTL-Segmentation

Meta Transfer Learning for Few Shot Semantic Segmentation using U-Net

Language: Python - Size: 290 KB - Last synced at: about 1 year ago - Pushed at: over 4 years ago - Stars: 21 - Forks: 6

clintonreece/keras-cloud-ml-engine

Adventures using keras on Google's Cloud ML Engine

Language: Python - Size: 4.47 MB - Last synced at: 5 months ago - Pushed at: about 8 years ago - Stars: 105 - Forks: 20

ncdisrup-ai/CreditCardFraudDetection

Detect fraudulent credit card transactions through supervised machine learning

Language: Jupyter Notebook - Size: 1.35 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

vaitybharati/NN_Hyperparameter-Tuning

Tuning of Hyperparameters :- Batch Size and Epochs. Tuning of Hyperparameters:- Learning rate and Drop out rate. Tuning of Hyperparameters:- Activation Function and Kernel Initializer. Tuning of Hyperparameter :-Number of Neurons in activation layer. Training model with optimum values of Hyperparameters.

Language: Jupyter Notebook - Size: 4.88 KB - Last synced at: over 1 year ago - Pushed at: over 4 years ago - Stars: 2 - Forks: 1

jwrr/shmoo-test

Sweep through ranges of command line hyperparameters to create testcases for multiple corners

Language: Python - Size: 19.5 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

ethanhezhao/matlab_gibbs_lda

Language: Matlab - Size: 2.93 KB - Last synced at: almost 2 years ago - Pushed at: over 8 years ago - Stars: 0 - Forks: 0

HenrikVarmer/textRec

textRec utlizes Latent Dirichlet Allocation and Jensen-Shannon-Divergence on the discrete probability distributions over LDA topics per document, in order to recommend unique and novel documents to specific users.

Language: R - Size: 124 KB - Last synced at: almost 2 years ago - Pushed at: about 4 years ago - Stars: 0 - Forks: 0

michalwols/hp

A python library for managing Hyperparameters

Language: Python - Size: 10.7 KB - Last synced at: about 1 month ago - Pushed at: about 3 years ago - Stars: 5 - Forks: 2

anishLearnsToCode/improving-deep-neural-networks

Coursera Course: Improving Deep Neural Networks, part of the Deep Learning Specialization ~deeplearning.ai

Language: Jupyter Notebook - Size: 25.5 MB - Last synced at: about 2 months ago - Pushed at: over 4 years ago - Stars: 4 - Forks: 1

anuj1312/credit-card-fraud-detection

Tuning XGBoost hyper-parameters with Simulated Annealing

Language: Jupyter Notebook - Size: 272 KB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 0

bbopt/HyperNOMAD

A library for the hyperparameter optimization of deep neural networks

Language: C++ - Size: 950 KB - Last synced at: over 1 year ago - Pushed at: over 3 years ago - Stars: 17 - Forks: 1

mirkomantovani/Machine-Learning-empathy-prediction

Final project for CS 412 Machine Learning at University of Illinois at Chicago

Language: Jupyter Notebook - Size: 15.4 MB - Last synced at: almost 2 years ago - Pushed at: over 6 years ago - Stars: 0 - Forks: 0

mbthales/hyperparameter-tuning

A Hyperparameter Tuning algorithm.

Language: Python - Size: 12.7 KB - Last synced at: about 1 year ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 0

rohan-varma/neuralnets

🤖 bare-bones implementation of a neural network with numpy

Language: Jupyter Notebook - Size: 13.1 MB - Last synced at: about 1 month ago - Pushed at: over 6 years ago - Stars: 16 - Forks: 8

FKENZOLS/classification_disease_project

ML classification project.

Language: Jupyter Notebook - Size: 5.05 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 0

crosstherubicon/Backprop_Hyper-parameters

Understanding hyperparameters of neural network architectures using 3 cost functions, 3 activation functions, 2 regularizations and dropout.

Language: Jupyter Notebook - Size: 1.63 MB - Last synced at: almost 2 years ago - Pushed at: over 4 years ago - Stars: 1 - Forks: 1

Octavian-ai/learning-rates

How optimizer and learning rate choice affects training performance

Language: Python - Size: 2.74 MB - Last synced at: almost 2 years ago - Pushed at: about 7 years ago - Stars: 21 - Forks: 8

mbiparva/ax-bo-image-classification

Hyperpatameter Bayesian Optimization for Image Classification in PyTorch

Language: Python - Size: 15.6 KB - Last synced at: about 2 years ago - Pushed at: almost 6 years ago - Stars: 9 - Forks: 1

JohnNay/forecastVeg

A Machine Learning Approach to Forecasting Remotely Sensed Vegetation Health in Python

Language: Python - Size: 3.62 MB - Last synced at: about 1 year ago - Pushed at: over 4 years ago - Stars: 45 - Forks: 21

Tjstretchalot/ignite-simple

Fast prototyping of machine learning models

Language: Python - Size: 5.82 MB - Last synced at: 18 days ago - Pushed at: about 2 years ago - Stars: 2 - Forks: 1

bhattbhavesh91/svm-c-gamma-hyperparameters-tutorial

In this video, I'll try to explain the hyperparameters C & Gamma in Support Vector Machine (SVM) in the simplest possible way.

Language: Jupyter Notebook - Size: 146 KB - Last synced at: about 2 months ago - Pushed at: about 4 years ago - Stars: 5 - Forks: 1

SirBob01/NeuralC

C++ library for implementing deep feed-forward neural networks (DFF)

Language: C++ - Size: 870 KB - Last synced at: over 2 years ago - Pushed at: about 4 years ago - Stars: 2 - Forks: 0

PatWie/RobustKernelPaths

ICML paper: Robust and Efficient Kernel Hyperparameter Paths with Guarantees

Language: C++ - Size: 31.3 KB - Last synced at: 2 months ago - Pushed at: over 2 years ago - Stars: 2 - Forks: 1

fau-masters-collected-works-cgarbin/dropout-vs-batch-normalization

Dropout vs. batch normalization: effect on accuracy, training and inference times - code for the paper

Language: TeX - Size: 2.25 MB - Last synced at: about 1 year ago - Pushed at: over 2 years ago - Stars: 8 - Forks: 1

hug-0/gnarl

Gnarl - An easy to use Deep Learning framework for Python

Language: Jupyter Notebook - Size: 47.9 KB - Last synced at: over 2 years ago - Pushed at: over 8 years ago - Stars: 3 - Forks: 0

KSpiliop/Fraud_Detection

Tuning XGBoost hyper-parameters with Simulated Annealing

Language: Jupyter Notebook - Size: 463 KB - Last synced at: over 2 years ago - Pushed at: about 8 years ago - Stars: 44 - Forks: 14

jakesherman/titanic-kaggle

Introductory Kaggle competition

Language: Jupyter Notebook - Size: 76.2 KB - Last synced at: over 2 years ago - Pushed at: almost 9 years ago - Stars: 7 - Forks: 10

Akash1070/Deploying-Machine-Learning-Models-via-Microsoft-Azure

Deploying Flight Price Prediction via Microsoft Azure

Language: HTML - Size: 400 KB - Last synced at: 3 months ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0

fitushar/Cyclical-Learning-Rates-for-Training-Neural-Networks-With-Unbalanced-Data-Sets

As the learning rate is one of the most important hyper-parameters to tune for training convolutional neural networks. In this paper, a powerful technique to select a range of learning rates for a neural network that named cyclical learning rate was implemented with two different skewness degrees. It is an approach to adjust where the value is cycled between a lower bound and upper bound. CLR policies are computationally simpler and can avoid the computational expense of fine tuning with fixed learning rate. It is clearly shown that changing the learning rate during the training phase provides by far better results than fixed values with similar or even smaller number of epochs.

Language: Jupyter Notebook - Size: 2.56 MB - Last synced at: 4 months ago - Pushed at: over 6 years ago - Stars: 3 - Forks: 0