Platform for Machine Learning projects on Software Engineering
Обновлено 2024-09-16 06:14:46 +03:00
A Repository for the public preview of Responsible AI in AML vNext
Обновлено 2024-09-13 01:24:07 +03:00
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
Обновлено 2024-09-13 00:12:52 +03:00
Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas to implementing productions. Qlib supports diverse machine learning modeling paradigms. including supervised learning, market dynamics modeling, and RL.
Обновлено 2024-09-12 18:44:27 +03:00
HI-ML toolbox for deep learning for medical imaging and Azure integration
Обновлено 2024-09-03 14:16:21 +03:00
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.
Обновлено 2024-08-29 21:13:51 +03:00
Hummingbird compiles trained ML models into tensor computation for faster inference.
Обновлено 2024-08-23 12:06:25 +03:00
The ORBIT dataset is a collection of videos of objects in clean and cluttered scenes recorded by people who are blind/low-vision on a mobile phone. The dataset is presented with a teachable object recognition benchmark task which aims to drive few-shot learning on challenging real-world data.
Обновлено 2024-08-13 03:27:45 +03:00
This package features data-science related tasks for developing new recognizers for Presidio. It is used for the evaluation of the entire system, as well as for evaluating specific PII recognizers or PII detection models.
Обновлено 2024-08-07 19:17:23 +03:00
Support ML teams to accelerate their model deployment to production leveraging Azure
Обновлено 2024-08-05 10:21:15 +03:00
this repo provides best practice guidance, plan template, solution assessment tool etc. to help Machine Learning Studio(classic) customer adopt Azure Machine Learning.
Обновлено 2024-07-23 05:46:51 +03:00
Python package for graph statistics
Обновлено 2024-07-23 01:36:30 +03:00
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
Обновлено 2024-07-03 13:54:08 +03:00
Using machine learning to detect beluga whale calls in hydrophone recordings
Обновлено 2024-06-18 01:58:02 +03:00
Common utilities for ONNX converters
Обновлено 2024-06-14 03:56:41 +03:00
Federated Learning Utilities and Tools for Experimentation
Обновлено 2024-01-11 22:20:09 +03:00
Accelerate your Neural Architecture Search (NAS) through fast, reproducible and modular research.
Обновлено 2023-12-22 22:29:11 +03:00
Toolkit for building machine learning models that generalize to unseen domains and are robust to privacy and other attacks.
Обновлено 2023-10-03 07:31:52 +03:00
Visuomotor policies from event-based cameras through representation learning and reinforcement learning. Accompanies our paper: https://arxiv.org/abs/2103.00806
Обновлено 2023-08-15 00:50:21 +03:00
Azure MLOps (v2) solution accelerators. Enterprise ready templates to deploy your machine learning models on the Azure Platform.
Обновлено 2023-07-28 08:11:02 +03:00
Examples of how to use or integrate DeepSpeech
Обновлено 2023-07-25 21:07:54 +03:00
Workshop for student hackathons focused on IoT dev
Обновлено 2023-07-25 12:28:46 +03:00
Self-training with Weak Supervision (NAACL 2021)
Обновлено 2023-07-25 01:35:52 +03:00
Cookiecutter template for testing Python scikit-learn regression learners.
Обновлено 2023-06-12 22:39:27 +03:00
Azure Machine Learning と GitHub を利用した MLOps のサンプルコード
Обновлено 2023-06-07 05:04:08 +03:00
Ready to use scoring engines for Image, Text and Time Series
Обновлено 2023-05-31 21:48:19 +03:00