83 Repositories
Latest Python Libraries
Y. Zhang, Q. Yao, W. Dai, L. Chen. AutoSF: Searching Scoring Functions for Knowledge Graph Embedding. IEEE International Conference on Data Engineering (ICDE). 2020
AutoSF The code for our paper "AutoSF: Searching Scoring Functions for Knowledge Graph Embedding" and this paper has been accepted by ICDE2020. News:
The code for our paper "AutoSF: Searching Scoring Functions for Knowledge Graph Embedding"
AutoSF The code for our paper "AutoSF: Searching Scoring Functions for Knowledge Graph Embedding" and this paper has been accepted by ICDE2020. News:
Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.
AutoViz Automatically Visualize any dataset, any size with a single line of code. AutoViz performs automatic visualization of any dataset with one lin
Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost Models on Time Series data sets with a Single Line of Code. Now updated with Dask to handle millions of rows.
Auto_TS: Auto_TimeSeries Automatically build multiple Time Series models using a Single Line of Code. Now updated with Dask. Auto_timeseries is a comp
Automatically Build Multiple ML Models with a Single Line of Code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.
Auto-ViML Automatically Build Variant Interpretable ML models fast! Auto_ViML is pronounced "auto vimal" (autovimal logo created by Sanket Ghanmare) N
Build tensorflow keras model pipelines in a single line of code. Created by Ram Seshadri. Collaborators welcome. Permission granted upon request.
deep_autoviml Build keras pipelines and models in a single line of code! Table of Contents Motivation How it works Technology Install Usage API Image
MLBox is a powerful Automated Machine Learning python library.
MLBox is a powerful Automated Machine Learning python library. It provides the following features: Fast reading and distributed data preprocessing/cle
A curated list of automated deep learning (including neural architecture search and hyper-parameter optimization) resources.
Awesome AutoDL A curated list of automated deep learning related resources. Inspired by awesome-deep-vision, awesome-adversarial-machine-learning, awe
The MLOps platform for innovators π
β DS2.ai is an integrated AI operation solution that supports all stages from custom AI development to deployment. It is an AI-specialized platform service that collects data, builds a training datas
Automated machine learning: Review of the state-of-the-art and opportunities for healthcare
Automated machine learning: Review of the state-of-the-art and opportunities for healthcare
A full pipeline AutoML tool for tabular data
HyperGBM Doc | δΈζ We Are HiringοΌ Dear folks,we are offering challenging opportunities located in Beijing for both professionals and students who are k
Hypernets: A General Automated Machine Learning framework to simplify the development of End-to-end AutoML toolkits in specific domains.
A General Automated Machine Learning framework to simplify the development of End-to-end AutoML toolkits in specific domains.
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
Master status: Development status: Package information: TPOT stands for Tree-based Pipeline Optimization Tool. Consider TPOT your Data Science Assista
An open source python library for automated feature engineering
"One of the holy grails of machine learning is to automate more and more of the feature engineering process." β Pedro Domingos, A Few Useful Things to
Books, Presentations, Workshops, Notebook Labs, and Model Zoo for Software Engineers and Data Scientists wanting to learn the TF.Keras Machine Learning framework
Books, Presentations, Workshops, Notebook Labs, and Model Zoo for Software Engineers and Data Scientists wanting to learn the TF.Keras Machine Learning framework
Primitives for machine learning and data science.
An Open Source Project from the Data to AI Lab, at MIT MLPrimitives Pipelines and primitives for machine learning and data science. Documentation: htt
Lale is a Python library for semi-automated data science.
Lale is a Python library for semi-automated data science. Lale makes it easy to automatically select algorithms and tune hyperparameters of pipelines that are compatible with scikit-learn, in a type-
CATE: Computation-aware Neural Architecture Encoding with Transformers
CATE: Computation-aware Neural Architecture Encoding with Transformers Code for paper: CATE: Computation-aware Neural Architecture Encoding with Trans
code for paper "Does Unsupervised Architecture Representation Learning Help Neural Architecture Search?"
Does Unsupervised Architecture Representation Learning Help Neural Architecture Search? Code for paper: Does Unsupervised Architecture Representation
Image Classification - A research on image classification and auto insurance claim prediction, a systematic experiments on modeling techniques and approaches
A research on image classification and auto insurance claim prediction, a systematic experiments on modeling techniques and approaches
[v1 (ISBI'21) + v2] MedMNIST: A Large-Scale Lightweight Benchmark for 2D and 3D Biomedical Image Classification
MedMNIST Project (Website) | Dataset (Zenodo) | Paper (arXiv) | MedMNIST v1 (ISBI'21) Jiancheng Yang, Rui Shi, Donglai Wei, Zequan Liu, Lin Zhao, Bili
Simple, fast, and parallelized symbolic regression in Python/Julia via regularized evolution and simulated annealing
Parallelized symbolic regression built on Julia, and interfaced by Python. Uses regularized evolution, simulated annealing, and gradient-free optimization.
Milano is a tool for automating hyper-parameters search for your models on a backend of your choice.
Milano (This is a research project, not an official NVIDIA product.) Documentation https://nvidia.github.io/Milano Milano (Machine learning autotuner
AutoDeeplab / auto-deeplab / AutoML for semantic segmentation, implemented in Pytorch
AutoML for Image Semantic Segmentation Currently this repo contains the only working open-source implementation of Auto-Deeplab which, by the way out-
Seach Losses of our paper 'Loss Function Discovery for Object Detection via Convergence-Simulation Driven Search', accepted by ICLR 2021.
CSE-Autoloss Designing proper loss functions for vision tasks has been a long-standing research direction to advance the capability of existing models
[SIGMETRICS 2022] One Proxy Device Is Enough for Hardware-Aware Neural Architecture Search
One Proxy Device Is Enough for Hardware-Aware Neural Architecture Search paper | website One Proxy Device Is Enough for Hardware-Aware Neural Architec
Automatic learning-rate scheduler
AutoLRS This is the PyTorch code implementation for the paper AutoLRS: Automatic Learning-Rate Schedule by Bayesian Optimization on the Fly published
A simple and lightweight genetic algorithm for optimization of any machine learning model
geneticml This package contains a simple and lightweight genetic algorithm for optimization of any machine learning model. Installation Use pip to ins
A simple and lightweight genetic algorithm for optimization of any machine learning model
geneticml This package contains a simple and lightweight genetic algorithm for optimization of any machine learning model. Installation Use pip to ins
An open source python library for automated feature engineering
"One of the holy grails of machine learning is to automate more and more of the feature engineering process." β Pedro Domingos, A Few Useful Things to
PyAF is an Open Source Python library for Automatic Time Series Forecasting built on top of popular pydata modules.
PyAF (Python Automatic Forecasting) PyAF is an Open Source Python library for Automatic Forecasting built on top of popular data science python module
Distributed Asynchronous Hyperparameter Optimization better than HyperOpt.
UltraOpt : Distributed Asynchronous Hyperparameter Optimization better than HyperOpt. UltraOpt is a simple and efficient library to minimize expensive
An AutoML survey focusing on practical systems.
This project is a community effort in constructing and maintaining an up-to-date beginner-friendly introduction to AutoML, focusing on practical systems. AutoML is a big field, and continues to grow
Sequential Model-based Algorithm Configuration
SMAC v3 Project Copyright (C) 2016-2018 AutoML Group Attention: This package is a reimplementation of the original SMAC tool (see reference below). Ho
Automated Machine Learning with scikit-learn
auto-sklearn auto-sklearn is an automated machine learning toolkit and a drop-in replacement for a scikit-learn estimator. Find the documentation here
Python based framework for Automatic AI for Regression and Classification over numerical data.
Python based framework for Automatic AI for Regression and Classification over numerical data. Performs model search, hyper-parameter tuning, and high-quality Jupyter Notebook code generation.
Deep Learning with PyTorch made easy π !
Deep Learning with PyTorch made easy π ! Carefree? carefree-learn aims to provide CAREFREE usages for both users and developers. It also provides a c
Code for the paper in Findings of EMNLP 2021: "EfficientBERT: Progressively Searching Multilayer Perceptron via Warm-up Knowledge Distillation".
This repository contains the code for the paper in Findings of EMNLP 2021: "EfficientBERT: Progressively Searching Multilayer Perceptron via Warm-up Knowledge Distillation".
PyTorch implementation of PNASNet-5 on ImageNet
PNASNet.pytorch PyTorch implementation of PNASNet-5. Specifically, PyTorch code from this repository is adapted to completely match both my implemetat
Python Automated Machine Learning library for tabular data.
Simple but powerful Automated Machine Learning library for tabular data. It uses efficient in-memory SAP HANA algorithms to automate routine Data Scie
AutoVideo: An Automated Video Action Recognition System
AutoVideo is a system for automated video analysis. It is developed based on D3M infrastructure, which describes machine learning with generic pipeline languages. Currently, it focuses on video actio
DeepHyper: Scalable Asynchronous Neural Architecture and Hyperparameter Search for Deep Neural Networks
What is DeepHyper? DeepHyper is a software package that uses learning, optimization, and parallel computing to automate the design and development of
An AutoML Library made with Optuna and PyTorch Lightning
An AutoML Library made with Optuna and PyTorch Lightning Installation Recommended pip install -U gradsflow From source pip install git+https://github.
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
H2O H2O is an in-memory platform for distributed, scalable machine learning. H2O uses familiar interfaces like R, Python, Scala, Java, JSON and the Fl
Kaggler is a Python package for lightweight online machine learning algorithms and utility functions for ETL and data analysis.
Kaggler is a Python package for lightweight online machine learning algorithms and utility functions for ETL and data analysis. It is distributed under the MIT License.
AutoML library for deep learning
Official Website: autokeras.com AutoKeras: An AutoML system based on Keras. It is developed by DATA Lab at Texas A&M University. The goal of AutoKeras
AutoTabular automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications.
AutoTabular automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications. With just a few lines of code, you can train and deploy high-accuracy m
Code for EMNLP 2021 main conference paper "Text AutoAugment: Learning Compositional Augmentation Policy for Text Classification"
Text-AutoAugment (TAA) This repository contains the code for our paper Text AutoAugment: Learning Compositional Augmentation Policy for Text Classific
Code for EMNLP 2021 main conference paper "Text AutoAugment: Learning Compositional Augmentation Policy for Text Classification"
Code for EMNLP 2021 main conference paper "Text AutoAugment: Learning Compositional Augmentation Policy for Text Classification"
This is a collection of our NAS and Vision Transformer work.
AutoML - Neural Architecture Search This is a collection of our AutoML-NAS work iRPE (NEW): Rethinking and Improving Relative Position Encoding for Vi
This is a collection of our NAS and Vision Transformer work.
This is a collection of our NAS and Vision Transformer work.
FLAML is a lightweight Python library that finds accurate machine learning models automatically, efficiently and economically
FLAML - Fast and Lightweight AutoML
This is a collection of our NAS and Vision Transformer work.
AutoML - Neural Architecture Search This is a collection of our AutoML-NAS work iRPE (NEW): Rethinking and Improving Relative Position Encoding for Vi
Lightwood is Legos for Machine Learning.
Lightwood is like Legos for Machine Learning. A Pytorch based framework that breaks down machine learning problems into smaller blocks that can be glu
Predictive AI layer for existing databases.
MindsDB is an open-source AI layer for existing databases that allows you to effortlessly develop, train and deploy state-of-the-art machine learning
Provide an input CSV and a target field to predict, generate a model + code to run it.
automl-gs Give an input CSV file and a target field you want to predict to automl-gs, and get a trained high-performing machine learning or deep learn
Automates Machine Learning Pipeline with Feature Engineering and Hyper-Parameters Tuning :rocket:
MLJAR Automated Machine Learning Documentation: https://supervised.mljar.com/ Source Code: https://github.com/mljar/mljar-supervised Table of Contents
Automated Machine Learning Pipeline with Feature Engineering and Hyper-Parameters Tuning
The mljar-supervised is an Automated Machine Learning Python package that works with tabular data. I
Naszilla is a Python library for neural architecture search (NAS)
A repository to compare many popular NAS algorithms seamlessly across three popular benchmarks (NASBench 101, 201, and 301). You can implement your ow
This repository contains FEDOT - an open-source framework for automated modeling and machine learning (AutoML)
package tests docs license stats support This repository contains FEDOT - an open-source framework for automated modeling and machine learning (AutoML