This is a fun, new monospaced font that includes programming ligatures and is designed to enhance the modern look and feel of the Windows Terminal.
Обновлено 2024-11-19 03:12:31 +03:00
TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data
Обновлено 2024-11-19 01:55:46 +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 2024-10-27 15:51:02 +03:00
Structured data files for topics covered by GitHub's Transparency Report
Обновлено 2024-09-30 19:42:54 +03:00
ETL jobs for Firefox Telemetry
Обновлено 2024-09-16 19:39:50 +03:00
Обновлено 2024-08-09 15:14:25 +03:00
Generic batch processing framework for managing the orchestration, dispatch, fault tolerance, and monitoring of arbitrary work items against many endpoints. Extensible via dependency injection. Includes examples against Cognitive Service containers for ML eval workloads.
Обновлено 2024-08-07 11:58:35 +03:00
Обновлено 2024-07-25 14:07:51 +03:00
Fit Sparse Synthetic Control Models in Python
Обновлено 2024-03-26 21:53:01 +03:00
WikiMo documentation (mainly the security space, but everyone's welcome to use this)
Обновлено 2024-01-17 19:53:19 +03:00
Spark bindings for Mozilla Telemetry
Обновлено 2023-11-09 13:04:44 +03:00
library for conducting propensity matching on spark scale
Обновлено 2023-06-27 16:02:06 +03:00
Обновлено 2023-06-12 21:47:21 +03:00
Automatically extracting keyphrases that are salient to the document meanings is an essential step to semantic document understanding. An effective keyphrase extraction (KPE) system can benefit a wide range of natural language processing and information retrieval tasks. Recent neural methods formulate the task as a document-to-keyphrase sequence-to-sequence task. These seq2seq learning models have shown promising results compared to previous KPE systems The recent progress in neural KPE is mostly observed in documents originating from the scientific domain. In real-world scenarios, most potential applications of KPE deal with diverse documents originating from sparse sources. These documents are unlikely to include the structure, prose and be as well written as scientific papers. They often include a much diverse document structure and reside in various domains whose contents target much wider audiences than scientists. To encourage the research community to develop a powerful neural model with key phrase extraction on open domains we have created OpenKP: a dataset of over 150,000 documents with the most relevant keyphrases generated by expert annotation.
Обновлено 2023-06-12 21:21:58 +03:00
This is an implementation of AAAI'20 paper "Semantics-Aligned Representation Learning for Person Re-identification". We leverages dense semantics to address both the spatial misalignment and semantics misalignment challenges in person re-identification.
Обновлено 2023-06-12 21:21:23 +03:00
Azure Synapse Spark Metrics provides easy metrics monitoring functions for Synapse services, especially, Apache Spark pool instances, by leveraging Prometheus, Grafana and Azure APIs.
Обновлено 2023-05-23 03:17:44 +03:00
Style-based Point Generator with Adversarial Rendering for Point Cloud Completion (CVPR 2021)
Обновлено 2023-04-19 00:04:59 +03:00
Cookiecutter API for creating Custom Skills for Azure Search using Python and Docker
Обновлено 2022-11-28 22:10:04 +03:00
This is the implementation of the TextNAS algorithm proposed in the paper TextNAS: A Neural Architecture Search Space tailored for Text Representation.
Обновлено 2022-11-28 22:09:08 +03:00
Qlib-Server is the data server system for Qlib. It enable Qlib to run in online mode. Under online mode, the data will be deployed as a shared data service. The data and their cache will be shared by all the clients. The data retrieval performance is expected to be improved due to a higher rate of cache hits. It will consume less disk space, too.
Обновлено 2022-07-08 05:15:09 +03:00
spaCy pipeline component for generating spaCy KnowledgeBase Alias Candidates for Entity Linking
Обновлено 2022-04-15 21:34:38 +03:00
FOST is a general forecasting tool, which demonstrate our experience and advanced technology in practical forecasting domains, including temporal, spatial-temporal and hierarchical forecasting. Current general forecasting tools (Gluon-TS by amazon, Prophet by facebook etc.) can not process and model structural graph data, especially in spatial domains, also those tools suffer from tradeoff between usability and accuracy. To address these challenges, we design and develop FOST and aims to empower engineers and data scientists to build high-accuracy and easy-usability forecasting tools.
Обновлено 2022-01-06 09:18:00 +03:00
📰 Fast, parallel feed updater for the News app; written in Python
Обновлено 2021-12-11 17:06:15 +03:00
GitHub Action that allows you to register models to your Azure Machine Learning Workspace.
Обновлено 2021-10-19 10:13:21 +03:00
GitHub Action that allows you to submit a run to your Azure Machine Learning Workspace.
Обновлено 2021-10-19 10:12:45 +03:00
GitHub Action that allows you to create or connect to your Azure Machine Learning Workspace.
Обновлено 2021-10-19 10:11:09 +03:00
GitHub Action that imports Databricks notebooks from a local path into the Databricks worspace
Обновлено 2021-10-01 00:29:00 +03:00
An automated and scalable approach to generate tasklets from a natural language task query and a website URL. Glider does not require any pre-training. Glider models tasklet extraction as a state space search, where agents can explore a website’s UI and get rewarded when making progress towards task completion. The reward is computed based on the agent’s navigating pattern and the similarity between its trajectory and the task query.
Обновлено 2021-09-03 06:52:47 +03:00
Source code for the "Copy that! Editing Sequences by Copying Spans" AAAI'21 paper
Обновлено 2021-06-14 17:34:00 +03:00
The WWT Aligner is a tool to match RGB images (JPEGs, TIFFs, etc) to scientific FITS images and annotate them with spatial information using AVM tags.
Обновлено 2021-06-02 20:36:04 +03:00