646 Open source projects that are alternatives of or similar to allie

Build tensorflow keras model pipelines in a single line of code. Now with mlflow tracking. Created by Ram Seshadri. Collaborators welcome. Permission granted upon request.

Time Series Forecasting Best Practices & Examples

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a delightful machine learning tool that allows you to train, test, and use models without writing code

BentoML Example Projects 🎨

Examples how MLJAR can be used

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

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📁 This repo makes it easy to download the raw audio files from AudioSet (32.45 GB, 632 classes).

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[ECCV 2018] AMC: AutoML for Model Compression and Acceleration on Mobile Devices

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

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

🚚 Agile Data Preparation Workflows made easy with Pandas, Dask, cuDF, Dask-cuDF, Vaex and PySpark

Tornado is a human-in-the-loop machine learning framework that helps you exploit your unlabelled data to train models through a simple and easy to use web interface.

Scripts to cleanup data from https://github.com/CSSEGISandData/COVID-19

MLModelScope is an open source, extensible, and customizable platform to facilitate evaluation and measurement of ML models within AI pipelines.

🚕 A spreadsheet-like data preparation web app that works over Optimus (Pandas, Dask, cuDF, Dask-cuDF, Spark and Vaex)

Korean Easy Data Augmentation

Extremely simple and fast extreme multi-class and multi-label classifiers.

A schema-aware Scala library for data transformation

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中国高等教育群体的心理健康状态数据集

An experimental Python package that reimplements AutoGBT using LightGBM and Optuna.

Generate embedding vectors from audio files

텍스트 요약 분야의 주요 연구 주제, Must-read Papers, 이용 가능한 model 및 data 등을 추천 자료와 함께 정리한 저장소입니다.

[ICLR'21] PyTorch code for our paper "Neural Pruning via Growing Regularization"

Search across publicly available datasets to find instances where a drug or cell line of interest has been profiled.

Three-Filters-to-Normal: An Accurate and Ultrafast Surface Normal Estimator (RAL+ICRA'21)

A high-performance Python-based I/O system for large (and small) deep learning problems, with strong support for PyTorch.

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🤖 PyTorch toolkit for biomedical imaging ❤️

The largest public catalogue for Arabic NLP and speech datasets. There are +250 datasets annotated with more than 25 attributes.

Elixir style pipe operator for Ruby

Two-stream CNN for gender classification and biometric identification using a dataset of 11K hand images.

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My solution to TUM's Machine Learning MNIST challenge 2016-2017 [winner]

Automated machine learning package

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Source code and data for ACL 2019 Long Paper ``Semantic Parsing with Dual Learning".

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A list of high quality open datasets for COVID-19 data analysis

AKShare is an elegant and simple financial data interface library for Python, built for human beings! 开源财经数据接口库

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Spark-Transformers: Library for exporting Apache Spark MLLIB models to use them in any Java application with no other dependencies.

AutoVideo: An Automated Video Action Recognition System

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A curated list of papers, code and resources pertaining to few-shot image generation.

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

Few-Shot-Intent-Detection includes popular challenging intent detection datasets with/without OOS queries and state-of-the-art baselines and results.

🌳 A curated list of ground-truth forest datasets for the machine learning and forestry community.

This repository contains datasets and code for the paper "HINT3: Raising the bar for Intent Detection in the Wild" accepted at EMNLP-2020's Insights Workshop https://insights-workshop.github.io/ Preprint for the paper is available here https://arxiv.org/abs/2009.13833