MLOS is a Data Science powered infrastructure and methodology to democratize and automate Performance Engineering. MLOS enables continuous, instance-based, robust, and trackable systems optimization.
Обновлено 2024-11-22 04:25:26 +03:00
Tools used for triaging performance bugs.
Обновлено 2024-11-18 03:14:56 +03:00
MonitoFi: Health & Performance Monitor for your Apache NiFi
Обновлено 2023-08-02 02:16:38 +03:00
View Adaptive Neural Networks for High Performance Skeleton-based Human Action Recognition
Обновлено 2023-06-12 21:55:25 +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
HPC Pack MESOS framework
Обновлено 2023-01-25 07:02:11 +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
tempeh is a framework to TEst Machine learning PErformance exHaustively which includes tracking memory usage and run time.
Обновлено 2022-01-04 00:15:32 +03:00
This project aims to predict the probability of leprosy using skin lesion images and clinical data (as compared to the diagnosis of dermatologists). This model is provided for research and development use only. The model is not intended for use in clinical decision-making or for any other clinical use and the performance of model for clinical use has not been established.
Обновлено 2021-06-30 03:06:06 +03:00
Model for detecting slow moving performance regressions
Обновлено 2020-08-19 20:05:58 +03:00
Repository for the scripts used in testing performance on Android and iOS
Обновлено 2019-08-06 15:43:29 +03:00
Class that calculates portfolio performance in USD given asset weights in portfolio, asset prices in different currencies and currencies rate to dollar.
Обновлено 2019-07-29 15:29:13 +03:00
Utilities for performance infrastructure
Обновлено 2017-09-14 11:21:51 +03:00