🏪 App Store for Nextcloud
Обновлено 2024-11-21 06:33:09 +03:00
🕶 addons.mozilla.org Django app and API 🎉
Обновлено 2024-11-21 00:51:47 +03:00
Mozilla's Localization Platform
Обновлено 2024-11-18 14:31:27 +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 2024-11-13 06:41:06 +03:00
Dockerized setup for ``mozilla-django-oidc`` local dev and testing
Обновлено 2024-10-29 21:18:55 +03:00
A Python package for generating concise, high-quality summaries of a probability distribution
Обновлено 2024-10-26 06:05:53 +03:00
Ongoing research training transformer language models at scale, including: BERT & GPT-2
Обновлено 2024-10-18 13:31:05 +03:00
Content Security Policy for Django.
Обновлено 2024-10-09 00:29:01 +03:00
The Microsoft SQL Server 3rd Party Backend for Django provides a connectivity layer for Django on SQL Server or Azure SQL DB.
Обновлено 2024-09-04 03:07:57 +03:00
Обновлено 2024-08-09 15:14:25 +03:00
Dataset of Government Open Source Policies
Обновлено 2024-07-06 05:15:10 +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
Product and locale details for Mozilla products
Обновлено 2024-06-26 13:16:58 +03:00
Multi-species bioacoustic classification using deep learning algorithms
Обновлено 2024-06-18 01:58:08 +03:00
A django OpenID Connect library
Обновлено 2024-03-12 15:24:16 +03:00
Sample code for the Django tutorial in the VS Code documentation
Обновлено 2024-02-28 00:45:57 +03:00
Multi-Agent Resource Optimization (MARO) platform is an instance of Reinforcement Learning as a Service (RaaS) for real-world resource optimization problems.
Обновлено 2024-02-23 11:45:58 +03:00
A fast algorithm to optimally compose privacy guarantees of differentially private (DP) mechanisms to arbitrary accuracy.
Обновлено 2024-02-15 16:24:04 +03:00
Sample Django+React+Postgres application for use in Visual Studio Code and Azure
Обновлено 2023-10-27 04:01:18 +03:00
A library for Go environment configuration in Sublime Text
Обновлено 2023-08-05 08:01:15 +03:00
An algorithm for cross-domain NL2SQL
Обновлено 2023-07-22 23:20:17 +03:00
Synthesizer for optimal collective communication algorithms
Обновлено 2023-07-21 21:16:40 +03:00
XTlib is an API and command line tool for scaling and managing ML experiments. The goal of XTLib is to enable you to effortlessly organize and scale your ML experiments. Our tools offer an incremental approach to adoption, so you can begin realizing benefits immediately..
Обновлено 2023-07-06 00:02:50 +03:00
A novel embedding training algorithm leveraging ANN search and achieved SOTA retrieval on Trec DL 2019 and OpenQA benchmarks
Обновлено 2023-06-13 00:27:31 +03:00
Code for the neural architecture search methods contained in the paper Efficient Forward Neural Architecture Search
Обновлено 2023-06-12 21:22:32 +03:00
Truly Conversational Search is the next logic step in the journey to generate intelligent and useful AI. To understand what this may mean, researchers have voiced a continuous desire to study how people currently converse with search engines. Traditionally, the desire to produce such a comprehensive dataset has been limited because those who have this data (Search Engines) have a responsibility to their users to maintain their privacy and cannot share the data publicly in a way that upholds the trusts users have in the Search Engines. Given these two powerful forces we believe we have a dataset and paradigm that meets both sets of needs: A artificial public dataset that approximates the true data and an ability to evaluate model performance on the real user behavior. What this means is we released a public dataset which is generated by creating artificial sessions using embedding similarity and will test on the original data. To say this again: we are not releasing any private user data but are releasing what we believe to be a good representation of true user interactions.
Обновлено 2023-06-12 21:21:58 +03:00
Обновлено 2023-06-12 21:12:54 +03:00