Search Results for "scikit-learn" - Page 15
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Showing 1969 open source projects for "scikit-learn"
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OpenClaw-RL
Train any agents simply by 'talking'
OpenClaw-RL is an open-source reinforcement learning framework designed to train and personalize AI agents built on the OpenClaw ecosystem. The project focuses on enabling agents to improve their behavior through interactive learning rather than relying solely on static prompts or predefined skills. One of its key ideas is allowing users to train an AI agent simply by interacting with it conversationally, using natural language feedback to guide the learning process. The system incorporates... -
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Generative AI for beginners with JS
Join a time-traveling adventure where you meet history’s legends
...The project is structured as a multi-lesson curriculum that introduces the concepts, tools, and practical techniques required to create generative AI applications. Each lesson includes written explanations, hands-on exercises, quizzes, and supporting videos to help developers learn the material progressively. Topics covered include prompt engineering, building AI-powered applications, working with structured outputs, integrating retrieval-augmented generation, and enabling tool or function calling in AI systems. The repository focuses specifically on how generative AI can be integrated into web, mobile, or desktop applications using JavaScript frameworks and APIs. -
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PRIME
Scalable RL solution for advanced reasoning of language models
...The system introduces the concept of process reinforcement through implicit rewards, allowing models to receive feedback on intermediate reasoning steps instead of evaluating only the final answer. This approach helps models learn better reasoning strategies and encourages them to generate more reliable multi-step solutions to complex tasks. PRIME provides training pipelines, datasets, and experimental infrastructure that allow researchers to train models with reinforcement learning tailored for reasoning improvement. The framework also includes data preprocessing utilities and example datasets such as mathematical reasoning tasks that are well suited for process-based reward signals. -
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AI Engineering Hub
In-depth tutorials on LLMs, RAGs and real-world AI agent applications
The AI Engineering Hub repository is a large open-source collection of hands-on projects, tutorials, and real-world AI engineering resources designed to help developers learn and build with modern AI technologies, especially large language models (LLMs), retrieval-augmented generation (RAG), and agent-based systems. It includes more than 90 production-ready projects across skill levels, organized into beginner, intermediate, and advanced categories to guide users progressively from simple experiments to complex AI workflows. ... -
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Agent Reinforcement Trainer
Train multi-step agents for real-world tasks using GRPO
Agent Reinforcement Trainer, or ART is an open-source reinforcement learning framework tailored to training large language model agents through experience, making them more reliable and performant on multi-turn, multi-step tasks. Instead of just manually crafting prompts or relying on supervised fine-tuning, ART uses techniques like Group Relative Policy Optimization (GRPO) to let agents learn from environmental feedback and reward signals. The framework is designed to integrate easily with Python applications, abstracting much of the RL infrastructure so developers can train agents without deep RL expertise or heavy infrastructure overhead. ART also supports scalable training patterns, observability tools, and integration with hosted platforms like Weights & Biases, and it provides notebooks that demonstrate training on standard benchmarks and tasks. -
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RSC Explorer
A tool for people curious about the React Server Components protocol
RSC Explorer is an educational, experiment-friendly tool for understanding the React Server Components (RSC) protocol by making the streaming process visible and inspectable. It runs both the “server” and “client” sides of RSC in the browser, removing the need to set up a full backend just to learn how the protocol behaves. The core experience is the ability to step through the RSC stream incrementally, seeing what data arrives at each moment and how that data maps to the React tree being constructed. It includes a set of curated examples that demonstrate how server and client features can interoperate, helping you develop intuition for boundaries, references, and progressive rendering. ... -
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Chinese-XLNet
Chinese XLNet pre-trained model
...Unlike traditional masked language modeling, XLNet uses a permutation language modeling objective that captures bidirectional context more effectively by training over all possible token orderings, yielding richer contextual representations. This model is trained on large-scale Chinese text datasets to learn linguistic patterns, long-range dependencies, and semantic nuance typical of Chinese writing, making it useful for tasks like text classification, question answering, named entity recognition, and language generation. Chinese-XLNet offers an alternative to models like BERT by emphasizing autoregressive and permutation-based learning, which can lead to performance improvements on certain benchmarks and tasks. -
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engineering-management
A collection of inspiring resources related to engineering management
...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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Best-websites-a-programmer-should-visit
Some useful websites for programmers
...Rather than being a random bookmark dump, it organizes resources into practical categories such as algorithms, competitive programming, reading materials, podcasts, newsletters, interview prep, design, security, performance, and more. The list aims to reduce the “what should I learn next?” friction by pointing you to high-signal, time-tested tutorials, references, and tools. Because it spans beginner to advanced topics, you can use it as an on-ramp when starting out and as a roadmap for deeper specialization later. It also surfaces non-code essentials like productivity, writing, and career guidance, acknowledging that strong developers need more than syntax. ... -
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Java Design Patterns Website
Next generation website for Java Design Patterns
...Because it’s built on VuePress, it benefits from a static-site workflow, theming, and easy deployment to GitHub Pages or similar hosting. It’s a good example of taking a large technical repo and giving it a documentation-first UI so newcomers can learn patterns without getting lost. -
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Hello Git & GitHub
Tutorial repository designed to teach how to use the Git vc system
...It is structured to introduce learners not only to the syntax of Git commands but also to development workflows such as feature branches, pull requests, and remote repositories. The content is hosted in a GitHub repository, reinforcing the practical aspect of versioning while you learn. It also includes supplemental materials like a book (in print and e-book) to complement the tutorials. This makes it highly useful for developers entering the open-source ecosystem or those needing a solid foundation in Git/GitHub workflow. -
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spf13-vim
The ultimate vim distribution
...The distribution standardizes plugin management and wiring so users don’t have to chase configuration snippets from blog posts. It emphasizes discoverability with well-documented mappings and a clear file layout, which helps newcomers learn the system and experienced users tweak it safely. Even though the broader Vim ecosystem has evolved, spf13-vim remains a recognizable snapshot of a cohesive, full-featured setup that many developers leaned on for years. Its value is as much educational as it is practical: it shows how to shape Vim into a modern editor while keeping the core lightweight and fast. -
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Mathematics Dataset
This dataset code generates mathematical question and answer pairs
...It generates question-and-answer pairs across a wide range of mathematical topics typically found in school-level curricula, testing a model’s ability to reason about algebra, arithmetic, calculus, probability, and more. Each question is programmatically generated with structured templates to ensure clear logic and reproducibility. The dataset enables models to learn mathematical problem-solving through examples that involve both numeric and symbolic reasoning. Version 1.0 includes over 2 million examples per category, with training splits labeled as “easy,” “medium,” and “hard,” supporting curriculum-based learning strategies. The data can be accessed via PyPI or generated locally using provided Python scripts, with outputs formatted for direct use in training or evaluation pipelines. -
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LKMPG
The Linux Kernel Module Programming Guide
lkmpg is a modernized, open-source guide that teaches the fundamentals of writing Linux kernel modules through clear explanations and working examples. It covers the full lifecycle: building and loading modules, understanding kernel symbols, handling device files, and interacting with kernel subsystems. Readers learn about concurrency concerns (spinlocks, mutexes), memory allocation in kernel space, and safe patterns for error handling and cleanup. The guide pairs narrative chapters with compilable code, so you can move from theory to practice and observe behavior directly with dmesg and friends. It also calls out pitfalls—like blocking in the wrong context or leaking references—that matter for stable, production-quality modules. ... -
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AIQuant
AI-powered platform for quantitative trading
ai_quant_trade is an AI-powered, one-stop open-source platform for quantitative trading—ranging from learning and simulation to actual trading. It consolidates stock trading knowledge, strategy examples, factor discovery, traditional rules-based strategies, various machine learning and deep learning methods, reinforcement learning, graph neural networks, high-frequency trading, C++ deployment, and Jupyter Notebook examples for practical hands-on use. Stock trading strategies: large models,... -
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Mem0
The Memory layer for AI Agents
...Mem0 is perfect for projects such as customer support, where chatbots remember past interactions to reduce repetition and speed up resolution times; personal AI companions that recall preferences and past conversations for more meaningful interactions; AI agents that learn from each interaction to become more personalized and effective over time. -
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Ancient Beast
The Turn Based Strategy Game/eSport. Master your beasts
Ancient Beast is a turn-based strategy indie game project played online against other people featuring a wide variety of creatures to acquire, putting them to use in order to defeat your opponents. This project was carefully designed to be easy to learn, fun to play and hard to master. We hope you'll enjoy it. The game takes place in a dystopian future, where people have excelled in power thanks to the use of technology, specifically advanced 3d printers. The world is split into 7 factions, based off the seven deadly sins (Avarice, Envy, Gluttony, Lust, Pride, Sloth, Wrath), fighting each other for resources, land, and supremacy. ... -
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Docspell
Assist in organizing your piles of documents
...If your documents are associated with such metadata, you can quickly find them later using the search feature. However adding this manually is a tedious task. Docspell can help by suggesting correspondents, guessing tags or finding dates using machine learning. It can learn metadata from existing documents and find things using NLP. This makes adding metadata to your documents a lot easier. For machine learning, it relies on the free (GPL) Stanford Core NLP library. -
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Instructor
Structured outputs for llms
...Instructor is trusted by engineers from platforms like Langflow, underscoring its reliability and effectiveness in managing structured outputs powered by LLMs. Instructor is powered by Pydantic, which is powered by type hints. Schema validation and prompting are controlled by type annotations; less to learn, and less code to write, and it integrates with your IDE. -
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A high-performance and flexible authorization/permission engine built for developers and inspired by Google Zanzibar. OpenFGA is designed to make it easy for developers to model their application permissions and add and integrate fine-grained authorization into their applications. It allows in-memory data storage for quick development, as well as pluggable database modules. It currently supports PostgreSQL 14, MySQL 8, and SQLite (currently in beta). It offers an HTTP API and a gRPC API. It...
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Chromatone
Chromatone is a digital garden of visual music theory
Cards and short overviews on the physics and physiology of vision and hearing and their intersection at visual music research, exploration, practice, and self-expression. Useful tools to have in the pocket like a pack of interactive cards to learn and use in everyday music practice. These are open source web experiments with different aspects of sound and color. Chromatone is an open source research and design project to explore, develop and implement the scientific way of visual music education, communication and performance. We've discovered complete and coherent Visual Music Language there. ... -
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Backpex
Backpex is a highly customizable administration panel for Phoenix Live
...Easily extendable with your own layouts, views, field types, filters, and more. Backpex comes with a rich set of features to quickly build a beautiful backoffice application. Visit the docs (coming soon) to learn about all the different possibilities. Easily add value metrics (like sums or averages) to your resources for a quick glance at your date. More metric types are in the making. -
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Neorg
Modernity meets insane extensibility
Neorg is an all-encompassing tool based around structured note taking, project and task management, time tracking, slideshows, writing typeset documents and much more. The premise is that all of these features are built on top of a single base file format (.norg), which the user only has to learn once to gain access to all of Neorg's functionality. Not only does this yield a low barrier for entry for new users it also ensures that all features are integrated with each other and speak the same underlying language. The file format is built to be expressive and easy to parse, which also makes .norg files easily usable anywhere outside of Neorg itself. ... -
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Functional programming library golang
functional programming library for golang
...Expose a consistent set of compositions to create new functions from existing ones. For each data type, there exists a small set of composition functions. These functions are called the same across all data types, so you only have to learn a small number of function names. The semantic of functions of the same name is consistent across all data types. -
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NeuralOperators.jl
DeepONets, Neural Operators, Physics-Informed Neural Ops in Julia
...It can be used to resolve partial differential equations (PDE). Instead of solving by finite element method, a PDE problem can be resolved by training a neural network to learn an operator mapping from infinite-dimensional space (u, t) to infinite-dimensional space f(u, t). Neural operator learns a continuous function between two continuous function spaces. The kernel can be trained on different geometry, which is learned from a graph. Fourier neural operator learns a neural operator with Dirichlet kernel to form a Fourier transformation. ...
