Python Automl-pipeline-selection Resources

Journey Towards Tiny Perceptual Super-Resolution Test code for our ECCV2020 paper: https://arxiv.org/abs/2007.04356 Our x4 upscaling pre-trained model

Corset is a web-based data selection portal that helps you getting relevant data from massive amounts of parallel data. So, if you don't need the whole corpus, but just a suitable subset (indeed, a cor(pus sub)set, this is what Corset will do for you--and the reason of the name of the tool.

SparseML is a toolkit that includes APIs, CLIs, scripts and libraries that apply state-of-the-art sparsification algorithms such as pruning and quantization to any neural network. General, recipe-driven approaches built around these algorithms enable the simplification of creating faster and smaller models for the ML performance community at large.

Clairvoyance: A Pipeline Toolkit for Medical Time Series Authors: van der Schaar Lab This repository contains implementations of Clairvoyance: A Pipel

upai-gst-dl-plugins Guide & Examples to create deeplearning gstreamer plugins and use them in your pipeline Introduction Thanks to the work done by @j

🍭 KRSH is Alpha version, so many bugs can be reported. If you find a bug, please write an Issue and grow the project together! A declarative Kubeflow

Synthetic Dataset Generator Authors: Stanislava Fedorova Alberto Tono Meher Shashwat Nigam Jiayao Zhang Amirhossein Ahmadnia Cecilia bolognesi Dominik

UnrealPerson: An Adaptive Pipeline for Costless Person Re-identification In our paper (arxiv), we propose a novel pipeline, UnrealPerson, that decreas

AWS Data Engineering Pipeline This is a repository for the Duke University Cloud Computing course project on Serverless Data Engineering Pipeline. For

UMS for Multi-turn Response Selection Implements the model described in the following paper Do Response Selection Models Really Know What's Next? Utte

An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.

Does Unsupervised Architecture Representation Learning Help Neural Architecture Search? Code for paper: Does Unsupervised Architecture Representation

AutoSF The code for our paper "AutoSF: Searching Scoring Functions for Knowledge Graph Embedding" and this paper has been accepted by ICDE2020. News:

The dataTap Python library is the primary interface for using dataTap's rich data management tools. Create datasets, stream annotations, and analyze model performance all with one library.

ETL Pipeline with Airflow, Spark, s3, MongoDB and Amazon Redshift

Parallelized symbolic regression built on Julia, and interfaced by Python. Uses regularized evolution, simulated annealing, and gradient-free optimization.

DARTS-PT Code accompanying the paper ICLR'2021: Rethinking Architecture Selection in Differentiable NAS Ruochen Wang, Minhao Cheng, Xiangning Chen, Xi

Modeling High-Frequency Limit Order Book Dynamics Using Machine Learning Framework to capture the dynamics of high-frequency limit order books. Overvi

Socorro Socorro is a Mozilla-centric ingestion pipeline and analysis tools for crash reports using the Breakpad libraries. Support This is a Mozilla-s

Pseudo-ISP: Learning Pseudo In-camera Signal Processing Pipeline from A Color Image Denoiser Abstract The success of deep denoisers on real-world colo

The mljar-supervised is an Automated Machine Learning Python package that works with tabular data. I

DESlib DESlib is an easy-to-use ensemble learning library focused on the implementation of the state-of-the-art techniques for dynamic classifier and

combo: A Python Toolbox for Machine Learning Model Combination Deployment & Documentation & Stats Build Status & Coverage & Maintainability & License

Pytorch-toolbelt A pytorch-toolbelt is a Python library with a set of bells and whistles for PyTorch for fast R&D prototyping and Kaggle farming: What

NVIDIA DALI The NVIDIA Data Loading Library (DALI) is a library for data loading and pre-processing to accelerate deep learning applications. It provi

Ray provides a simple, universal API for building distributed applications. Ray is packaged with the following libraries for accelerating machine lear

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

Deep GNN, Shallow Sampling Hanqing Zeng, Muhan Zhang, Yinglong Xia, Ajitesh Srivastava, Andrey Malevich, Rajgopal Kannan, Viktor Prasanna, Long Jin, R

Overview Nidaba is the central controller for the entire OGL OCR pipeline. It oversees and automates the process of converting raw images into citable

DeepSceneTextReader This is a c++ project deploying a deep scene text reading pipeline. It reads text from natural scene images. Prerequsites The proj

Real-time-Scene-Text-Detection-and-Recognition-System End-to-end pipeline for real-time scene text detection and recognition. The detection model use

Toy Machine Learning Pipeline Table of Contents About Getting Started ML task description and evaluation procedure Dataset description Repository stru

SMAC v3 Project Copyright (C) 2016-2018 AutoML Group Attention: This package is a reimplementation of the original SMAC tool (see reference below). Ho

sklearn-genetic Genetic feature selection module for scikit-learn Genetic algorithms mimic the process of natural selection to search for optimal valu

Master status: Development status: Package information: scikit-rebate This package includes a scikit-learn-compatible Python implementation of ReBATE,

BoostARoota A Fast XGBoost Feature Selection Algorithm (plus other sklearn tree-based classifiers) Why Create Another Algorithm? Automated processes l

boruta_py This project hosts Python implementations of the Boruta all-relevant feature selection method. Related blog post How to install Install with

scikit-feature Feature selection repository scikit-feature in Python. scikit-feature is an open-source feature selection repository in Python develope

"One of the holy grails of machine learning is to automate more and more of the feature engineering process." ― Pedro Domingos, A Few Useful Things to

BatchFlow BatchFlow helps you conveniently work with random or sequential batches of your data and define data processing and machine learning workflo

pdpipe ˨ Easy pipelines for pandas DataFrames (learn how!). Website: https://pdpipe.github.io/pdpipe/ Documentation: https://pdpipe.github.io/pdpipe/d

Yellowbrick Visual analysis and diagnostic tools to facilitate machine learning model selection. What is Yellowbrick? Yellowbrick is a suite of visual

MLBox is a powerful Automated Machine Learning python library. It provides the following features: Fast reading and distributed data preprocessing/cle

auto-sklearn auto-sklearn is an automated machine learning toolkit and a drop-in replacement for a scikit-learn estimator. Find the documentation here

Master status: Development status: Package information: TPOT stands for Tree-based Pipeline Optimization Tool. Consider TPOT your Data Science Assista

Time series analysis today is an important cornerstone of quantitative science in many disciplines, including natural and life sciences as well as eco

DaCy: A SpaCy NLP Pipeline for Danish DaCy is a Danish preprocessing pipeline trained in SpaCy. At the time of writing it has achieved State-of-the-Ar

The latest information about Galaxy can be found on the Galaxy Community Hub. Community support is available at Galaxy Help. Galaxy Quickstart Galaxy

Model search (MS) is a framework that implements AutoML algorithms for model architecture search at scale. It aims to help researchers speed up their exploration process for finding the right model architecture for their classification problems (i.e., DNNs with different types of layers).

CSE-Autoloss Designing proper loss functions for vision tasks has been a long-standing research direction to advance the capability of existing models

Text preprocessing, representation and visualization from zero to hero. From zero to hero • Installation • Getting Started • Examples • API • FAQ • Co

This repository contains custom pipes and models related to using spaCy for scientific documents. In particular, there is a custom tokenizer that adds

spacy-transformers: Use pretrained transformers like BERT, XLNet and GPT-2 in spaCy This package provides spaCy components and architectures to use tr

✨ NeuralCoref 4.0: Coreference Resolution in spaCy with Neural Networks. NeuralCoref is a pipeline extension for spaCy 2.1+ which annotates and resolv

AutoViz Automatically Visualize any dataset, any size with a single line of code. AutoViz performs automatic visualization of any dataset with one lin

AudioTK Audio ToolKit is a set of audio filters. It helps assembling workflows for specific audio processing workloads. The audio workflow is split in

PipeLayer is a lightweight Python pipeline framework. Define a series of steps, and chain them together to create modular applications

Text preprocessing, representation and visualization from zero to hero. From zero to hero • Installation • Getting Started • Examples • API • FAQ • Co

This repository contains custom pipes and models related to using spaCy for scientific documents. In particular, there is a custom tokenizer that adds

spacy-transformers: Use pretrained transformers like BERT, XLNet and GPT-2 in spaCy This package provides spaCy components and architectures to use tr

✨ NeuralCoref 4.0: Coreference Resolution in spaCy with Neural Networks. NeuralCoref is a pipeline extension for spaCy 2.1+ which annotates and resolv

Haystack is an end-to-end framework for Question Answering & Neural search that enables you to ... ... ask questions in natural language and find gran

AutoViz Automatically Visualize any dataset, any size with a single line of code. AutoViz performs automatic visualization of any dataset with one lin

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

mongo-connector The mongo-connector project originated as a MongoDB mongo-labs project and is now community-maintained under the custody of YouGov, Pl

Pipeline Pipeline is an asset packaging library for Django, providing both CSS and JavaScript concatenation and compression, built-in JavaScript templ

UltraOpt : Distributed Asynchronous Hyperparameter Optimization better than HyperOpt. UltraOpt is a simple and efficient library to minimize expensive

Soda SQL Data testing, monitoring and profiling for SQL accessible data. What does Soda SQL do? Soda SQL allows you to Stop your pipeline when bad dat

Pipeline Pipeline is an asset packaging library for Django, providing both CSS and JavaScript concatenation and compression, built-in JavaScript templ

MLJAR Automated Machine Learning Documentation: https://supervised.mljar.com/ Source Code: https://github.com/mljar/mljar-supervised Table of Contents

Lightwood is like Legos for Machine Learning. A Pytorch based framework that breaks down machine learning problems into smaller blocks that can be glu

Neuraxle Pipelines Code Machine Learning Pipelines - The Right Way. Neuraxle is a Machine Learning (ML) library for building machine learning pipeline

Master status: Development status: Package information: TPOT stands for Tree-based Pipeline Optimization Tool. Consider TPOT your Data Science Assista

auto_ml Automated machine learning for production and analytics Installation pip install auto_ml Getting started from auto_ml import Predictor from au

Steppy What is Steppy? Steppy is a lightweight, open-source, Python 3 library for fast and reproducible experimentation. Steppy lets data scientist fo

Auto-ViML Automatically Build Variant Interpretable ML models fast! Auto_ViML is pronounced "auto vimal" (autovimal logo created by Sanket Ghanmare) N

igel A delightful machine learning tool that allows you to train/fit, test and use models without writing code Note I'm also working on a GUI desktop

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

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

Ray provides a simple, universal API for building distributed applications. Ray is packaged with the following libraries for accelerating machine lear