Search Results for "strategy"
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997 projects for "strategy" with 2 filters applied:
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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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Backtrack Sampler
An easy-to-understand framework for LLM samplers
Backtrack Sampler is a framework designed for experimenting with custom sampling strategies for language models (LLMs), enabling the ability to rewind and revise generated tokens. It allows developers to create and test their own token generation strategies by providing a base structure for manipulating logits and probabilities, making it a flexible tool for those interested in fine-tuning the behavior of LLMs. -
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DeepSeek-V3
Powerful AI language model (MoE) optimized for efficiency/performance
...It employs Multi-head Latent Attention (MLA) and the DeepSeekMoE architecture to enhance computational efficiency. The model introduces an auxiliary-loss-free load balancing strategy and a multi-token prediction training objective to boost performance. Trained on 14.8 trillion diverse, high-quality tokens, DeepSeek-V3 underwent supervised fine-tuning and reinforcement learning to fully realize its capabilities. Evaluations indicate that it outperforms other open-source models and rivals leading closed-source models, achieving this with a training duration of 55 days on 2,048 Nvidia H800 GPUs, costing approximately $5.58 million. -
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BenchmarkTools.jl
A benchmarking framework for the Julia language
...The CI infrastructure for automated performance testing of the Julia language is not in this package but can be found in Nanosoldier.jl. Our story begins with two packages, "Benchmarks" and "BenchmarkTrackers". The Benchmarks package implemented an execution strategy for collecting and summarizing individual benchmark results, while BenchmarkTrackers implemented a framework for organizing, running, and determining regressions of groups of benchmarks. Under the hood, BenchmarkTrackers relied on Benchmarks for actual benchmark execution. -
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MathModel
Mathematical Modeling for Graduate Students, Mathematical Modeling
MathModel is a repository dedicated to collecting and organizing resources around mathematical modeling, especially for university students preparing for modeling competitions (e.g. undergraduate and graduate levels). The content spans exemplary competition papers, algorithmic solutions, LaTeX templates, presentation slides, MATLAB tutorials, and mind maps of modeling approaches. It acts as a centralized archive where learners can access high-quality past solutions as references, borrow... -
The ultimate digital workspace.Hundreds of companies and millions of employees use Axero’s intranet software to communicate, collaborate, manage tasks and events, organize content, and develop their company culture.
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Telos
Telos is an open-sourced framework for creating Deep Context
Telos is an open-sourced framework designed to help individuals, organisations, or even planetary-scale entities articulate what they are about and how they intend to pursue their purpose. It encourages capturing a “context file” that outlines mission, goals, problems, strategies, KPIs, and other core components of meaningful work. The project emphasises creating deep context about matters that humans care about, making underlying intentions explicit rather than implicit. It is structured so... -
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engineering-management
A collection of inspiring resources related to engineering management
...Rather than being a generic management reading list, it collects content that speaks directly to leading software teams, managing projects, and supporting engineers’ growth. The materials span topics like one-on-ones, feedback, hiring, performance reviews, culture, strategy, and remote work. The maintainer highlights articles that are short, concrete, and packed with actionable ideas, making it easier for busy managers to learn without wading through entire books first. Many entries come from experienced leaders sharing hard-won lessons, so the list doubles as a mentorship proxy for new managers. It is especially useful for individual contributors transitioning into management, or for existing managers who want to benchmark and refine their practices. -
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Laravel Feature Flags
A Laravel package for handling feature flags
A Feature flag is at times referred to as a feature toggle or feature switch. Ultimately it's a coding strategy to be used along with source control to make it easier to continuously integrate and deploy. The idea of the flags works by essentially safeguarding sections of code from executing if a feature flag isn't in a switched-on state. This package aims to make implementing such flags across your application a great deal easier by providing solutions that work with not only your code but also your routes, blade files, task scheduling, and validations. -
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JetCache
JetCache is a Java cache framework
JetCache is a Java cache abstraction that provides uniform usage for different caching solutions. It provides more powerful annotations than those in Spring Cache. The annotations in JetCache support native TTL, two-level caching, and automatically refresh in distributed environments, also you can manipulate Cache instances by your code. Currently, there are four implementations: RedisCache, TairCache(not open source on github), CaffeineCache (in memory) and a simple LinkedHashMapCache (in... -
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DreamO
A Unified Framework for Image Customization
...DreamO’s design introduces a feature routing constraint that helps disentangle different control conditions (like identity, style, clothing) when more than one is specified, which significantly reduces conflicts and artifacts when combining controls. It also uses a “placeholder strategy” to precisely align conditional inputs (e.g. where to place clothing or objects) in generated images, giving users fine-grained control over composition. -
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AI Hedge Fund
An AI Hedge Fund Team
This repository demonstrates how to build a simplified, automated hedge fund strategy powered by AI/ML. It integrates financial data collection, preprocessing, feature engineering, and predictive modeling to simulate decision-making in trading. The code shows workflows for pulling stock or market data, applying machine learning algorithms to forecast trends, and generating buy/sell/hold signals based on the predictions. -
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Design Patterns in Swift
Design Patterns implemented in Swift
Design-Patterns-In-Swift is a repository that translates classic software engineering design patterns (from sources like the Gang of Four) into Swift code examples, so you can see how those patterns look in a modern, strongly typed, object-/protocol-oriented language. It covers creational, structural, and behavioral patterns: singletons, factories, decorators, observers, strategy, command, mediator, and more. For each pattern, you’ll typically see one or more Swift implementations, commentary on where it makes sense in a Swift architecture, and caveats about when you might prefer pure protocol composition or using functional patterns instead. The examples aim to be readable and idiomatic—not overly abstract or contrived—so developers can adopt or adapt them directly. -
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FinRobot
An Open-Source AI Agent Platform for Financial Analysis using LLMs
...It provides developers and quants with structured modules to fetch market data, process time series, generate technical indicators, and construct features appropriate for machine learning models, while also supporting backtesting and evaluation metrics to measure strategy performance. Built with modularity in mind, FinRobot allows users to plug in custom models — from classical algorithms to deep learning architectures — and orchestrate components in pipelines that can run reproducibly across experiments. The framework also tends to include automation layers for deployment, enabling trained models to operate in live or simulated environments with scheduled re-training and risk controls in place. -
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StructuralEquationModels.jl
A fast and flexible Structural Equation Modelling Framework
...You can choose to mix loss functions natively found in this package and those you provide. In such cases, you optimize over a sum of different objectives (e.g. ML + Ridge). This strategy also applies to gradients, where you may supply analytic gradients or opt for automatic differentiation or mixed analytical and automatic differentiation. You may consider using this package if you need extensibility and/or speed, and if you want to extend SEM. -
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AI-Job-Notes
AI algorithm position job search strategy
AI-Job-Notes is a pragmatic notebook for landing roles in machine learning, computer vision, and related engineering tracks. It assembles study paths, checklists, and interview prep materials, but also covers job-search mechanics—portfolio building, resume patterns, and communication tips. The emphasis is on doing: practicing with project ideas, setting up reproducible experiments, and showcasing results that convey impact. It ties technical study (ML/DL fundamentals) to real hiring signals... -
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RoaringBitmap
A better compressed bitset in Java
Bitsets, also called bitmaps, are commonly used as fast data structures. Unfortunately, they can use too much memory. To compensate, we often use compressed bitmaps. Roaring bitmaps are compressed bitmaps which tend to outperform conventional compressed bitmaps such as WAH, EWAH or Concise. In some instances, roaring bitmaps can be hundreds of times faster and they often offer significantly better compression. They can even be faster than uncompressed bitmaps. -
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Optopsy
A nimble options backtesting library for Python
...Optopsy is a small simple library that offloads the heavy work of backtesting option strategies, the API is designed to be simple and easy to implement into your regular Panda's data analysis workflow. As such, we just need to call the long_calls() function to have Optopsy generate all combinations of a simple long call strategy for the specified time period and return a DataFrame. Here we also use Panda's round() function afterwards to return statistics within two decimal places. -
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Poetiq
Reproduction of Poetiq's record-breaking submission to the ARC-AGI-1
...The project demonstrates a system that orchestrates large language models (LLMs) — like those from major providers — with carefully engineered prompting, reasoning workflows, and dynamic strategies, to tackle the abstract, logic-heavy problems in ARC-AGI. Instead of relying on a single prompt or fixed strategy, their solver dynamically adapts the reasoning path, selecting what to ask or analyze next depending on intermediate results — effectively compositing reasoning, perception, and program synthesis (or symbolic manipulation) in a loop. The repository allows others to reproduce their results, experiment with different LLM backends (e.g. the user may supply keys for supported models), and observe how their adaptive meta-system handles the logic and abstraction challenges. -
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DeiT (Data-efficient Image Transformers)
Official DeiT repository
DeiT (Data-efficient Image Transformers) shows that Vision Transformers can be trained competitively on ImageNet-1k without external data by using strong training recipes and knowledge distillation. Its key idea is a specialized distillation strategy—including a learnable “distillation token”—that lets a transformer learn effectively from a CNN or transformer teacher on modest-scale datasets. The project provides compact ViT variants (Tiny/Small/Base) that achieve excellent accuracy–throughput trade-offs, making transformers practical beyond massive pretraining regimes. Training involves carefully tuned augmentations, regularization, and optimization schedules to stabilize learning and improve sample efficiency. ... -
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React Router
Declarative routing for React
React Router is a standards‑focused, multi‑strategy routing library for React applications, offering both full‑framework capabilities and lightweight, flexible library usage. It enables robust routing experiences across React versions. It supports advanced features in React 19. You can use it maximally as a React framework or minimally as a library with your own architecture. First‑class type safety with automatic type generation for route params and data. -
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PokeeResearch-7B
Pokee Deep Research Model Open Source Repo
...Instead of relying only on static training data, the agent performs searches, visits pages, and extracts evidence before forming answers to complex queries. It is built to operate end-to-end: planning a research strategy, gathering sources, reasoning over conflicting claims, and writing a grounded response. The repository includes evaluation results on multi-step QA and research benchmarks, illustrating how web-time context boosts accuracy. Because the system is modular, you can swap the search component, reader, or policy to fit private deployments or different data domains. ... -
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Universal Tool Calling Protocol (UTCP)
Official python implementation of UTCP. UTCP is an open standard
The python-utcp repository is the official Python SDK implementation of the Universal Tool Calling Protocol (UTCP). UTCP is an open, modern standard designed to let AI agents call any tool or API directly—over HTTP, CLI, WebSocket, gRPC, and more—without the overhead of extra wrapper layers or middleware. It leverages a modular, plugin-based architecture built around Pydantic models and separates the core functionality into a lightweight client and extensible protocol plugins, enabling... -
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VibeThinker
Diversity-driven optimization and large-model reasoning ability
VibeThinker is a compact but high-capability open-source language model released by WeiboAI (Sina AI Lab). It contains about 1.5 billion parameters, far smaller than many “frontier” models, yet it is explicitly optimized for reasoning, mathematics, and code generation tasks rather than general open-domain chat. The innovation lies in its training methodology: the team uses what they call the Spectrum-to-Signal Principle (SSP), where a first stage emphasizes diversity of reasoning paths (the... -
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Front-End Performance Checklist
The only Front-End Performance Checklist that runs faster
Front-End-Performance-Checklist is a comprehensive, developer-friendly guide that consolidates the most impactful client-side performance practices into a single, scannable resource. It frames performance as a front-end responsibility and turns broad principles into concrete, verifiable checks you can apply before shipping. The checklist is organized by areas such as HTML, CSS, JavaScript, fonts, images, and network delivery, so teams can tackle bottlenecks systematically. Each section... -
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Elixir Code Smells
Catalog of Elixir-specific code smells
...Initially compiled via grey literature (blogs, talks, forums), the catalog now includes 23 Elixir-specific smells plus 12 traditional smells adapted to Elixir. Each entry documents the name, category, problem, example, refactoring strategy, and step-by-step treatments. The smells are grouped into two categories: design-related (coarse-grained, harder to detect, affecting architecture/processes) and low-level concerns (fine-grained, often readability and maintainability issues). The catalog evolves with community feedback and contributions, aiming to help developers recognize harmful patterns and apply disciplined refactoring to improve maintainability, testability, and performance in Elixir systems. -
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openctp
Provides CTP stock options and Zhongtai Securities XTP
openctp is a technical service platform built around the CTP trading ecosystem that provides CTP compatible interfaces for a wide range of brokerage backends and markets. Its core idea is to wrap heterogeneous stock and derivatives trading gateways such as Zhongtai XTP, Huaxin Qidian TORA, and others with CTPAPI compatible interfaces, so existing CTP programs can connect simply by swapping dynamic libraries rather than rewriting code. The project offers a comprehensive simulation environment...