Search Results for "tasks" - Page 8
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537 projects for "tasks" with 2 filters applied:
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Save Up to 91% on Cloud Compute With Spot VMsRun batch jobs at 60-91% off with Spot VMs. Long-running workloads get automatic discounts with sustained use.
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Cut Data Warehouse Costs by 54%BigQuery delivers 54% lower TCO with exabyte scale and flexible pricing. Free migration tools handle the SQL translation automatically.
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Sheeeeeeeeet
Sheeeeeeeeet is a Swift library for creating menus
Sheeeeeeeeet is a UIKit library that lets you create menus that can be presented as custom action sheets, context menus, alert controllers, or in any way you like. Sheeeeeeeeet comes with many item types (standard items, buttons, titles, toggles, etc.) and can be extended with your own custom item types. Since I have personally moved over to SwiftUI, this repository is no longer under active development. I will however gladly merge any PRs that add value to it or fixes problems with new iOS... -
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iJEPA
Official codebase for I-JEPA
...The design scales naturally with Vision Transformer backbones and flexible masking strategies, and it trains stably at large batch sizes. i-JEPA’s predictions are made in embedding space, which is computationally efficient and better aligned with downstream discrimination tasks. The repository provides training recipes, data pipelines, and evaluation code that clarify which masking patterns and architectural choices matter most. -
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React Projects
Collection of React example / tutorial projects
...Each project is self-contained and demonstrates specific techniques—hooks for state and effects, context for global state, custom hooks for reuse, and reducer patterns for complex updates. The codebases include common UI tasks like forms, modals, lists, filtered search, and pagination, along with data fetching and basic routing where appropriate. Because every project focuses on a narrow set of concepts, learners can clone a single folder, run it, and grasp the idea without wading through a monolith. The examples are structured to be approachable yet idiomatic, encouraging good habits while staying close to what developers actually build. ... -
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KADOS
KADOS is a full post-it web-based tool for SCRUM or Agile projects
KADOS (KAnban Dashboard for Online Scrum) is a web-based tool for managing Scrum projects. Its particularity is to provide maximum screens where the user can move his post-it to change one of the attributes of these post-it Kados supports artifacts of SCRUM method, but it can also be adapted for other agile methods. Kados is available in French, English, Spanish, German and Brazilian Portuguese Visit http://www.kados.info/welcome-on-kados-site/ for latest news KADOS est un outil web... -
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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KotlinDL
High-level Deep Learning Framework written in Kotlin
...KotlinDL offers simple APIs for training deep learning models from scratch, importing existing Keras and ONNX models for inference, and leveraging transfer learning for tailoring existing pre-trained models to your tasks. This project aims to make Deep Learning easier for JVM and Android developers and simplify deploying deep learning models in production environments. -
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Lumen PHP Framework
The Laravel Lumen Framework.
Laravel Lumen is a stunningly fast PHP micro-framework for building web applications with expressive, elegant syntax. We believe development must be an enjoyable, creative experience to be truly fulfilling. Lumen attempts to take the pain out of development by easing common tasks used in the majority of web projects, such as routing, database abstraction, queueing, and caching. -
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conc
Better structured concurrency for go
Conc is a Go library for managing structured concurrency, simplifying the development of concurrent applications with high performance. -
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Learning Prompt
Free prompt engineering online course
Learning-Prompt is a curated repository of prompts, techniques, and instructional patterns designed to help people construct better prompts for AI systems, including generation, reasoning, and debugging tasks. It collects examples of effective prompt formats, chains of thought, strategy scaffolds, and comparative methods that help yield consistent, high-quality results. The project also includes meta-guidance: reflections on prompt failures, tips for prompt tuning, ways to mitigate model bias or misinterpretation, and how to adapt prompts for different AI capabilities. ... -
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emacs-ng
A new approach to Emacs
...One of its key innovations is the ability to run JavaScript code within Emacs using embedded engines, enabling new forms of interaction and extension development. Emacs-ng also explores concurrency improvements, allowing certain tasks to execute asynchronously without blocking the editor’s main thread, which enhances responsiveness. The project includes support for compiling extensions to native code, improving execution speed compared to traditional Emacs Lisp. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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albert_zh
Implementation of A Lite Bert For Self-Supervised Learning Language
...The project includes several model variants, such as tiny, small, base, large, and xlarge-style releases, giving users options for speed, size, and accuracy tradeoffs. It also provides guidance for fine-tuning downstream tasks such as sentence-pair semantic similarity and Chinese classification benchmarks. The repository includes support paths for TensorFlow, PyTorch conversion, Keras loading, TensorFlow 2.0 loading, and TensorFlow Lite deployment for mobile scenarios. Overall, it is useful for Chinese NLP developers who need compact pretrained language models for classification, similarity, and other language understanding tasks. -
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Reinforcement-learning
Implementation of Reinforcement Learning Algorithms. Python, OpenAI
...The project collects popular approaches such as dynamic programming, Monte Carlo methods, temporal difference learning, Q-learning, SARSA, deep Q-networks, and policy gradient techniques, often demonstrated with Python and OpenAI Gym environments so users can experiment with agents learning in simulated tasks. For each algorithm category, the repository pairs conceptual descriptions with runnable code and often illustrated exercises that help solidify understanding by bridging theory with practice. It’s structured to serve learners progressing from basic tabular methods to function approximation and deep learning extensions, making it suitable for students, researchers, or practitioners exploring reinforcement learning fundamentals. -
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Facexlib
FaceXlib aims at providing ready-to-use face-related functions
facexlib is a PyTorch-based library providing ready-to-use face-related functions, including detection, alignment, recognition, and more. It integrates state-of-the-art open-source methods for various face processing tasks. -
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Cancelable Async Flows
Cancelable Async Flows (CAF)
CAF (Cancelable Async Flows) is a small utility that brings cooperative cancellation to JavaScript async workflows. It wraps async generators or promise-returning functions so they can respond to a cancel signal and halt work early, preventing wasted CPU and stray side effects. The library encourages a disciplined pattern: pass a token into your task, periodically check it, and unwind gracefully when cancellation is requested. This approach avoids brittle timeouts and “fire-and-forget” leaks... -
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MessageThrottle
A lightweight Objective-C message throttle and debounce library
MessageThrottle is a runtime Objective-C library that allows developers to throttle or debounce Objective-C messages (method calls). It helps optimize performance by limiting the frequency of method executions, useful in scenarios like UI updates or event handling. -
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Official YOLOv7
YOLOv7: Trainable bag-of-freebies sets new state-of-the-art
...YOLOv7 introduced training-time improvements that raise accuracy without increasing inference cost, which is why the project became important in real-time detection research. It supports multiple model sizes and related tasks such as object detection and instance segmentation through associated branches or weights. It is useful for researchers, engineers, and developers building detection systems for video, edge devices, robotics, analytics, and industrial vision. -
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With the JServiceServer you can provide services over a network via http (like web services) without any XML-overhead. It has been developed for small computer systems like Java-microcontrollers.
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pyTorch Tutorials
Build your neural network easy and fast
...The project is structured around clear, executable Python scripts and Jupyter notebooks that demonstrate regression, classification, convolutional networks, recurrent networks, autoencoders, and generative adversarial networks, which gives learners practical exposure to real machine learning tasks. Each example explains PyTorch’s dynamic computation graph, optimization techniques, and core abstractions in a way that is accessible and reproducible. Contributors and authors integrate visual and coded examples so readers can see both the theory and the implementation side-by-side. -
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Job-DSL Gradle Example
An example Job DSL project that uses Gradle for building and testing
...It provides example DSL scripts that generate Jenkins jobs, and integrates them into a Gradle build for automated job generation, testing, and validation. Configurable job definitions (folders, branches, parameters). Tests for DSL scripts to validate generated XML. Integration with Gradle tasks for generation & testing. Support for seeding Jenkins or updating via REST API. Reuse and modularization of DSL logic. -
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DeepLabv3 Plus
Encoder-Decoder with Atrous Separable Convolution
...The project also supports multi-GPU training, multiple backbones, learning rate schedules with step and cosine options, optimizer selection, and adaptive learning rate behavior based on batch size. It is useful for users who want a stronger semantic segmentation baseline than U-Net for scene-level segmentation tasks. -
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Google Cloud Vision API examples
Sample code for Google Cloud Vision
The cloud-vision repository is a sample code collection for the Google Cloud Vision API that shows developers how to implement image analysis tasks across a wide range of languages and platforms. It contains examples organized by language and environment, including Go, Java, Node.js, PHP, Python, Ruby, .NET, Android, iOS, and even a Chrome extension, which makes it especially valuable as a cross-platform learning resource. The repository demonstrates concrete image understanding use cases, such as landmark detection and mobile photo analysis with label and face detection, so developers can see how Vision API outputs are consumed in real interfaces and workflows. ... -
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Terminals Are Sexy
A curated list of Terminal frameworks, plugins & resources
...It pulls together high-quality links to terminal emulators, shells, prompts, plugins, fonts, color schemes, and command-line utilities, alongside learning materials for sharpening everyday CLI skills. The list favors practical, well-maintained projects and is organized so you can quickly discover alternatives for common tasks (navigation, search, networking, monitoring, text processing, and more). It also points to customization ideas—prompts, themes, and fonts—that help you craft a clear, legible, and pleasant environment. Because it’s a living list, contributions are encouraged, keeping entries current as tools evolve. If you spend time in a terminal—whether writing code, administering systems, or just automating chores—this is a single, convenient place to find better defaults and new favorites. -
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Laravel Initializer
Install and update Laravel application with single command
Install and update the Laravel application with a single command. Outdated repository, check out the updated link. We all know, that every application should contain a readme file and an Installation section with a list of actions that you should to do prepare an application to work. Some of actions you should do on every application update (composer update, git pull...) or branch change (git checkout) for preparing an application to work. Laravel Initializer gives you the ability to declare... -
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Model Search
Framework that implements AutoML algorithms
...Instead of hand-crafting models, you define a search space and objectives, then the system explores candidate architectures using controllers and population-based strategies. It supports multiple tasks (such as vision or text) by letting you express reusable building blocks—layers, cells, and topologies—that the search can recombine. Training, evaluation, and promotion of candidates are orchestrated automatically, with strong emphasis on reproducibility and fair comparisons. The framework logs trials, metrics, and artifacts so you can analyze what the search learned and why certain designs dominate. ... -
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Svelte forms lib
A lightweight library for managing forms in Svelte
Svelte Forms lib is a Formik-inspired library for building forms easily in a Svelte project. When building modern web applications forms often play a big part in it. We use forms to log in, place orders, book flights and perform other data-entry tasks. In developing a form, it's important to create a flow that guides the user efficiently and effectively through the workflow. This library helps you build forms by exposing an easy API for form creation, validation and submission. -
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Mixin
Mixin is a trait/mixin and bytecode weaving framework for Java
...Additional documentation for individual features and annotations can be found in the extensive Javadoc. For additional help use the channel #mixin on the Sponge Discord Server. For handling obfuscation tasks, Mixin provides an Annotation Processor which works at compile time to generate obfuscation mappings for your toolchain to apply. If using Gradle 5 or later, annotation processors are no longer automatically loaded from compile configurations and must be specified explicitly via annotationProcessor configurations.
