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129 search results found

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

Wandb ⭐ 8,204

🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.

Auto Sklearn ⭐ 7,262

Automated Machine Learning with scikit-learn

Skypilot ⭐ 4,975

SkyPilot: Run LLMs, AI, and Batch jobs on any cloud. Get maximum savings, highest GPU availability, and managed execution—all with a simple interface.

Determined ⭐ 2,715

Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning, experiment tracking, and resource management. Works with PyTorch and TensorFlow.

Scikit Optimize ⭐ 2,700

Sequential model-based optimization with a `scipy.optimize` interface

Forecasting ⭐ 2,540

Time Series Forecasting Best Practices & Examples

Coursera Deep Learning Specialization ⭐ 2,459

Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models

Rl Baselines3 Zoo ⭐ 1,640

A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.

Talos ⭐ 1,596

Hyperparameter Optimization for TensorFlow, Keras and PyTorch

Xcessiv ⭐ 1,232

A web-based application for quick, scalable, and automated hyperparameter tuning and stacked ensembling in Python.

Vizier ⭐ 1,142

Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.

Hyperparameter Optimization Of Machine Learning Algorithms ⭐ 1,025

Implementation of hyperparameter optimization/tuning methods for machine learning & deep learning models (easy&clear)

Rl Baselines Zoo ⭐ 1,025

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

SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization

Onepanel ⭐ 707

The open source, end-to-end computer vision platform. Label, build, train, tune, deploy and automate in a unified platform that runs on any cloud and on-premises.

EvalML is an AutoML library written in python.

OCTIS: Comparing Topic Models is Simple! A python package to optimize and evaluate topic models (accepted at EACL2021 demo track)

Hyperparameter_hunter ⭐ 635

Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries

Neuraxle ⭐ 533

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.

Hyperband ⭐ 515

Tuning hyperparams fast with Hyperband

Human-explainable AI.

Tune Sklearn ⭐ 461

A drop-in replacement for Scikit-Learn’s GridSearchCV / RandomizedSearchCV -- but with cutting edge hyperparameter tuning techniques.

Agilerl ⭐ 457

Streamlining reinforcement learning with RLOps

Automl Implementation For Static And Dynamic Data Analytics ⭐ 443

Implementation/Tutorial of using Automated Machine Learning (AutoML) methods for static/batch and online/continual learning

Optunity ⭐ 343

optimization routines for hyperparameter tuning

Syne Tune ⭐ 342

Large scale and asynchronous Hyperparameter and Architecture Optimization at your fingertips.

Hyperboard ⭐ 327

A web-based dashboard for Deep Learning

Library for Semi-Automated Data Science

Hyperparameter optimization that enables researchers to experiment, visualize, and scale quickly.

Parallel Hyperparameter Tuning in Python

Deeplearning.ai Notes ⭐ 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.

Library for automatic retraining and continual learning

Hypernets ⭐ 256

A General Automated Machine Learning framework to simplify the development of End-to-end AutoML toolkits in specific domains.

Auptimizer ⭐ 195

An automatic ML model optimization tool.

Sentence Classification ⭐ 180

Sentence Classifications with Neural Networks

Pyaudioprocessing ⭐ 175

Audio feature extraction and classification

Automl_alex ⭐ 171

State-of-the art Automated Machine Learning python library for Tabular Data

The Data Science Workshop ⭐ 156

A New, Interactive Approach to Learning Data Science

Adatune ⭐ 144

Gradient based Hyperparameter Tuning library in PyTorch

PyXAB - A Python Library for X-Armed Bandit and Online Blackbox Optimization Algorithms

Milano is a tool for automating hyper-parameters search for your models on a backend of your choice.

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

Metadata store for Production ML

Distribution transparent Machine Learning experiments on Apache Spark

Hyperopt Keras Cnn Cifar 100 ⭐ 87

Auto-optimizing a neural net (and its architecture) on the CIFAR-100 dataset. Could be easily transferred to another dataset or another classification task.

Hyperparameter tuning for machine learning models using a distributed genetic algorithm

Black box hyperparameter optimization made easy.

Purely functional genetic algorithms for multi-objective optimisation

Mlprimitives ⭐ 67

Primitives for machine learning and data science.

Pre-trained Gaussian processes for Bayesian optimization

Open Box ⭐ 64

Generalized and Efficient Blackbox Optimization System.

Clsurvey ⭐ 61

Continual Hyperparameter Selection Framework. Compares 11 state-of-the-art Lifelong Learning methods and 4 baselines. Official Codebase of "A continual learning survey: Defying forgetting in classification tasks." in IEEE TPAMI.

Hypertune ⭐ 60

A library for performing hyperparameter optimization

Tfestimators ⭐ 59

R interface to TensorFlow Estimators

Mindware ⭐ 54

An efficient open-source AutoML system for automating machine learning lifecycle, including feature engineering, neural architecture search, and hyper-parameter tuning.

Iterated Racing for Automatic Algorithm Configuration

Ds Ml Public ⭐ 49

Python Scripts and Jupyter Notebooks

Scikit Hyperband ⭐ 46

A scikit-learn compatible implementation of hyperband

Mlr3tuning ⭐ 46

Hyperparameter optimization package of the mlr3 ecosystem

The Deep Learning With Keras Workshop ⭐ 40

An Interactive Approach to Understanding Deep Learning with Keras

Map Floodwater Satellite Imagery ⭐ 31

This repository focuses on training semantic segmentation models to predict the presence of floodwater for disaster prevention. Models were trained using SageMaker and Colab.

Estimation of Distribution algorithms Python package

An abstraction layer for parameter tuning

Spark Parameter Optimization and Tuning

Kerastuner ⭐ 29

R interface to Keras Tuner

Wandb Offline Sync Hook ⭐ 26

A convenient way to trigger synchronizations to wandb / Weights & Biases if your compute nodes don't have internet!

Auto Surprise ⭐ 25

An AutoRecSys library for Surprise. Automate algorithm selection and hyperparameter tuning 🚀

Machine Learning Tool Box

Propulate ⭐ 24

Propulate is an asynchronous evolutionary optimization algorithm and software package for global optimization and hyperparameter search on high-performance computers.

Hyperparameter search for AllenNLP - powered by Ray TUNE

Flexible Bayesian Optimization in R

Differential Privacy Bayesian Optimization ⭐ 22

This repo contains the underlying code for all the experiments from the paper: "Automatic Discovery of Privacy-Utility Pareto Fronts"

Performs Variables selection and model tuning for Species Distribution Models (SDMs). It provides also several utilities to display results.

Global, derivative-free optimization for hyperparameter tuning

skrobot is a Python module for designing, running and tracking Machine Learning experiments / tasks. It is built on top of scikit-learn framework.

Black-box optimization framework for R.

Cerebro System ⭐ 18

Data System for Optimized Deep Learning Model Selection

Diviner is a serverless machine learning and hyper parameter tuning platform

Mlr3hyperband ⭐ 17

Successive Halving and Hyperband in the mlr3 ecosystem

Naturalselection ⭐ 16

A general-purpose pythonic genetic algorithm.

Hpbandster Sklearn ⭐ 15

A scikit-learn wrapper for HpBandSter hyper parameter search.

Dl4j Rnn Timeseries Examples ⭐ 15

An example of DL4J's Recurrent Neural Networks applied to timeseries data

Hyperparameters Optimization ⭐ 14

Hyperparameters-Optimization

Xgboost Lightgbm Hyperparameter Tuning ⭐ 14

Bayesian Optimization and Grid Search for xgboost/lightgbm

GUI for Keras and TensorFlow with integrated hyperparameter optimization and NLP

Nlpboost ⭐ 14

Python library for automatic training, optimization and comparison of Transformer models on most NLP tasks.

Cs230_dl ⭐ 13

♊ Stanford CS230 : Deep Learning

Awesome Auto Ml ⭐ 13

Awesome list of AutoML frameworks - curated by @oskar-j

Hypertune ⭐ 12

Hyperparameter tuning using Particle Swarm Optimization and parallel computation which outperforms current approaches. V0.1 Beta

Neuralnets ⭐ 11

🤖 bare-bones implementation of a neural network with numpy

python experiment management toolset

[NeurIPS 2023] Multi-fidelity hyperparameter optimization with deep power laws that achieves state-of-the-art results across diverse benchmarks.

Hypernomad ⭐ 10

A library for the hyperparameter optimization of deep neural networks

Mlr3tuningspaces ⭐ 10

Collection of search spaces for hyperparameter optimization in the mlr3 ecosystem

Neural Networks And Deep Learning ⭐ 9

Deep learning projects including applications (face recognition, neural style transfer, autonomous driving, sign language reading, music generation, translation, speech recognition and NLP) and theories (CNNs, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, hyperparameter tuning, regularization, optimization, Residual Networks). Deep Learning Specialization by Andrew Ng, deeplearning.ai

Timeseriesgan ⭐ 9

GANs for Time series analysis (Synthetic data generation, anomaly detection and interpolation), Hypertuning using Optuna, MLFlow and Databricks

Prediction Of Solar Radiation ⭐ 9

Utilizing an Artificial Neural Network (ANN) based on Hyperparameter tuning, a new solution for Solar Radiation is approached.

Deeplearning.ai Deep Learning Specialization ⭐ 9

This repo contains my work & The code base for this Deep Learning Specialization offered by deeplearning.AI

Nli Calypso ⭐ 9

CS224n final project

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