217 Open source projects that are alternatives of or similar to Autokeras

A curated list of automated deep learning (including neural architecture search and hyper-parameter optimization) resources.

An AutoDL tool for Neural Architecture Search and Hyperparameter Optimization on Tensorflow and Keras

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

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

AutoGluon: AutoML for Text, Image, and Tabular Data

a distributed Hyperband implementation on Steroids

Genetic neural architecture search with Keras

AutoML frAmework for Neural Networks

"NAS evaluation is frustratingly hard", ICLR2020

Differentiable architecture search for convolutional and recurrent networks

Naszilla is a Python library for neural architecture search (NAS)

Towards Automated Deep Learning: Efficient Joint Neural Architecture and Hyperparameter Search https://arxiv.org/abs/1807.06906

PyTorch implementation of PNASNet-5 on ImageNet

Official Implementation of 'Fast AutoAugment' in PyTorch.

AutoML for image augmentation. AutoAlbument uses the Faster AutoAugment algorithm to find optimal augmentation policies. Documentation - https://albumentations.ai/docs/autoalbument/

An open source python library for automated feature engineering

TensorFlow implementation of PNASNet-5 on ImageNet

A specially designed light version of Fast AutoAugment

TransmogrifAI (pronounced trăns-mŏgˈrə-fī) is an AutoML library for building modular, reusable, strongly typed machine learning workflows on Apache Spark with minimal hand-tuning

Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.

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

[InterSpeech 2020] "AutoSpeech: Neural Architecture Search for Speaker Recognition" by Shaojin Ding*, Tianlong Chen*, Xinyu Gong, Weiwei Zha, Zhangyang Wang

Sequential Model-based Algorithm Configuration

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

💹 SIMON is powerful, flexible, open-source and easy to use machine learning knowledge discovery platform 💻

This repo is about NAS

Codebase for "AutoPrognosis: Automated Clinical Prognostic Modeling via Bayesian Optimization", ICML 2018.

Automated Deep Learning without ANY human intervention. 1'st Solution for AutoDL [email protected]

[UNMAINTAINED] Automated machine learning- just give it a data file! Check out the production-ready version of this project at ClimbsRocks/auto_ml

MLBox is a powerful Automated Machine Learning python library.

Automated deep learning algorithms implemented in PyTorch.

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

Code for the neural architecture search methods contained in the paper Efficient Forward Neural Architecture Search

[UNMAINTAINED] Automated machine learning for analytics & production

[CVPR 2020] MTL-NAS: Task-Agnostic Neural Architecture Search towards General-Purpose Multi-Task Learning

Fast and flexible AutoML with learning guarantees.

An automatic ML model optimization tool.

Linear Prediction Model with Automated Feature Engineering and Selection Capabilities

SGAS: Sequential Greedy Architecture Search (CVPR'2020) https://www.deepgcns.org/auto/sgas

Automated Machine Learning with scikit-learn

Library for Semi-Automated Data Science

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

Automatically Build Multiple ML Models with a Single Line of Code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.

Automated modeling and machine learning framework FEDOT

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

Efficient Learning of Augmentation Policy Schedules

Awesome Neural Architecture Search Papers

A simplified version of featuretools for Spark

An open source python library for automated feature engineering based on Genetic Programming

A fast and lightweight AutoML library.

Official PyTorch code for CVPR 2021 paper "AutoDO: Robust AutoAugment for Biased Data with Label Noise via Scalable Probabilistic Implicit Differentiation"

Encodings for neural architecture search

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.

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

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

LAMA - automatic model creation framework

(ICCV 2021) BossNAS: Exploring Hybrid CNN-transformers with Block-wisely Self-supervised Neural Architecture Search

collecting related resources of automated machine learning here

Fast & Simple Resource-Constrained Learning of Deep Network Structure

Implementation of: "Exploring Randomly Wired Neural Networks for Image Recognition"