124 Open source projects that are alternatives of or similar to Determined

PyTorch implementation of Proximal Gradient Algorithms a la Parikh and Boyd (2014). Useful for Auto-Sizing (Murray and Chiang 2015, Murray et al. 2019).

Auto-tune the Entropy Temperature of Soft Actor-Critic via Metagradient - 7th ICML AutoML workshop 2020

Intelligently optimizes technical indicators and optionally selects the least intercorrelated for use in machine learning models

Gradient based hyperparameter optimization & meta-learning package for TensorFlow

Python library for CMA Evolution Strategy.

Time Series Cross-Validation -- an extension for scikit-learn

Polyaxon Core Client & CLI to streamline MLOps

A hyperparameter optimization framework

DeepArchitect: Automatically Designing and Training Deep Architectures

AutoGluon: AutoML for Text, Image, and Tabular Data

MiraiML: asynchronous, autonomous and continuous Machine Learning in Python

Scalable, structured, dynamically-scheduled hyperparameter optimization.

Robyn is an experimental, automated and open-sourced Marketing Mix Modeling (MMM) package from Facebook Marketing Science. It uses various machine learning techniques (Ridge regression with cross validation, multi-objective evolutionary algorithm for hyperparameter optimisation, gradient-based optimisation for budget allocation etc.) to define m…

MIT DeepTraffic top 2% solution (75.01 mph) 🚗.

A library for doing Bayesian Optimization using Gaussian Processes (blackbox optimizer) in Go/Golang.

Easy Hyper Parameter Optimization with mlr and mlrMBO.

Notes for Deep Learning Specialization Courses led by Andrew Ng.

A Clojure machine learning library

Python library for Bayesian hyper-parameters optimization

Python code for bayesian optimization using Gaussian processes

A list of high-quality (newest) AutoML works and lightweight models including 1.) Neural Architecture Search, 2.) Lightweight Structures, 3.) Model Compression, Quantization and Acceleration, 4.) Hyperparameter Optimization, 5.) Automated Feature Engineering.

🦅Hyperparameter optimization for machine learning pipelines 🦅

Bilevel Optimization Library in Python for Multi-Task and Meta Learning

Hyperparameter optimization in Julia.

DeepHyper: Scalable Asynchronous Neural Architecture and Hyperparameter Search for Deep Neural Networks

A hyperparameter optimization and data collection toolbox for convenient and fast prototyping of machine-learning models.

A fully decentralized hyperparameter optimization framework

A curated list of awesome Distributed Deep Learning resources.

Autonomous Performance Tuning for Kubernetes !

A general, modular, and programmable architecture search framework

🚀 A demonstration of hyperparameter optimization using Optuna for models implemented with AllenNLP.

A simple, extensible library for developing AutoML systems

A web-based dashboard for Deep Learning

mlmodels : Machine Learning and Deep Learning Model ZOO for Pytorch, Tensorflow, Keras, Gluon models...

Data System for Optimized Deep Learning Model Selection

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

A shell-friendly hyperparameter search tool inspired by Optuna

Efficient Hyperparameter Optimization of Deep Learning Algorithms Using Deterministic RBF Surrogates

Distributed Asynchronous Hyperparameter Optimization better than HyperOpt. 比HyperOpt更强的分布式异步超参优化库。

[UNMAINTAINED] Automated machine learning for analytics & production

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

A toolset for black-box hyperparameter optimisation.

Diviner is a serverless machine learning and hyper parameter tuning platform

An Interactive Approach to Understanding Deep Learning with Keras

本人多次机器学习与大数据竞赛Top5的经验总结，满满的干货，拿好不谢

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

Gradient based Hyperparameter Tuning library in PyTorch

Hyperparameter Optimization for TensorFlow, Keras and PyTorch

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

A curated list of automated machine learning papers, articles, tutorials, slides and projects

Python library for CMA Evolution Strategy.

Examples for https://github.com/optuna/optuna

Sentence Classifications with Neural Networks

Human-explainable AI.

A friendly python package for Keras Hyperparameters Tuning based only on NumPy and hyperopt.

Your local Flux surgeon

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

Automated Machine Learning Pipeline with Feature Engineering and Hyper-Parameters Tuning 🚀

Iterated Racing for Automatic Algorithm Configuration

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.