Search Results for "apache framework"
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Showing 13 open source projects for "apache framework"
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The AI workplace management platformBy combining AI workflows, predictive intelligence, and automated insights, OfficeSpace gives leaders a complete view of how their spaces are used and how people work. Facilities, IT, HR, and Real Estate teams use OfficeSpace to optimize space utilization, enhance employee experience, and reduce portfolio costs with precision.
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Get full visibility and control over your tasks and projects with Wrike.Wrike offers world-class features that empower cross-functional, distributed, or growing teams take their projects from the initial request stage all the way to tracking work progress and reporting results.
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FATE
An industrial grade federated learning framework
FATE (Federated AI Technology Enabler) is the world's first industrial grade federated learning open source framework to enable enterprises and institutions to collaborate on data while protecting data security and privacy. It implements secure computation protocols based on homomorphic encryption and multi-party computation (MPC). Supporting various federated learning scenarios, FATE now provides a host of federated learning algorithms, including logistic regression, tree-based algorithms,... -
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DifferenceKit
A fast and flexible O(n) difference algorithm framework
A fast and flexible O(n) difference algorithm framework for Swift collection. The algorithm is optimized based on the Paul Heckel’s algorithm. This is a diffing algorithm developed for Carbon, works stand alone. The algorithm optimized based on the Paul Heckel’s algorithm. See also his paper A technique for isolating differences between files released in 1978. It allows all kind of diffs to be calculated in linear time O(n). RxDataSources and IGListKit are also implemented based on his... -
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Detectron2
Next-generation platform for object detection and segmentation
Detectron2 is Facebook AI Research's next generation software system that implements state-of-the-art object detection algorithms. It is a ground-up rewrite of the previous version, Detectron, and it originates from maskrcnn-benchmark. It is powered by the PyTorch deep learning framework. Includes more features such as panoptic segmentation, Densepose, Cascade R-CNN, rotated bounding boxes, PointRend, DeepLab, etc. Can be used as a library to support different projects on top of it. We'll... -
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frontend-interview
The strongest front-end interview guide in the universe
This is a review summary project about preparing for front-end interviews that I have summarized, and the project is updated from time to time. This is not only a strategy for job interviews, but also a collection of front-end ers to examine themselves and achieve breakthroughs. I hope that through this guide, everyone can open up their own lines of Ren and Du, and go further on the road to the front. This warehouse uses a large number of diagrams to convey knowledge. The so-called picture... -
Run applications fast and securely in a fully managed environmentRun frontend and backend services, batch jobs, deploy websites and applications, and queue processing workloads without the need to manage infrastructure.
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Coach
Enables easy experimentation with state of the art algorithms
Coach is a python framework that models the interaction between an agent and an environment in a modular way. With Coach, it is possible to model an agent by combining various building blocks, and training the agent on multiple environments. The available environments allow testing the agent in different fields such as robotics, autonomous driving, games and more. It exposes a set of easy-to-use APIs for experimenting with new RL algorithms and allows simple integration of new environments... -
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Dopamine
Framework for prototyping of reinforcement learning algorithms
Dopamine is a research framework for fast prototyping of reinforcement learning algorithms. It aims to fill the need for a small, easily grokked codebase in which users can freely experiment with wild ideas (speculative research). This first version focuses on supporting the state-of-the-art, single-GPU Rainbow agent (Hessel et al., 2018) applied to Atari 2600 game-playing (Bellemare et al., 2013). Specifically, our Rainbow agent implements the three components identified as most important... -
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Active Learning
Framework and examples for active learning with machine learning model
Active Learning is a Python-based research framework developed by Google for experimenting with and benchmarking various active learning algorithms. It provides modular tools for running reproducible experiments across different datasets, sampling strategies, and machine learning models. The system allows researchers to study how models can improve labeling efficiency by selectively querying the most informative data points rather than relying on uniformly sampled training sets. The main... -
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Physhun is a Java framework for building and executing finite state machines in J2SE and J2EE environments. State models are defined as collections of Spring beans, and do not use proprietary modeling languages. The framework is simple and flexible.
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Comet Backup - Fast, Secure Backup Software for MSPsComet is a flexible backup platform, giving you total control over your backup environment and storage destinations.
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Are Plain Old Java Objects (POJOs) to complex? The aim of this framework is, to convert JavaBeans (complex Java-Object graphs) in a simplified representation (JSON, XML, CSV or other object structures) or handle and control access to JavaBean properties.
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The Spiffy framework is a collection of often used helper methods and utility classes used in industry. Such methods and classes solves existing and re-ocuring practical problems and remedies annoying features of the Java language.
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The Gene Expression Programming Framework in Java. It separates the process of evolution from the process of interpretation of the chromosome, allowing the use of various schemes in the chromosome.
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