Search Results for "sarvesh-project" - Page 25
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Showing 3479 open source projects for "sarvesh-project"
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RL with PyTorch
Clean, Robust, and Unified PyTorch implementation
RL with PyTorch is a research-oriented repository that provides implementations of deep reinforcement learning algorithms using the PyTorch framework. The project focuses on helping developers and researchers understand reinforcement learning methods by providing clean and reproducible implementations of well-known algorithms. It includes code for popular deep reinforcement learning techniques such as Deep Q-Networks, policy gradient methods, actor-critic architectures, and other modern RL approaches. ... -
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Finance
150+ quantitative finance Python programs
Finance is a repository that compiles structured notes and educational material related to financial analysis, markets, and quantitative finance concepts. The project focuses on explaining key principles used in finance and investment analysis, including topics such as financial statements, valuation models, portfolio theory, and financial markets. The repository is designed as a study reference for students and professionals who want to understand financial systems and the analytical frameworks used in financial decision-making. ... -
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Data Science Articles from CodeCut
Collection of useful data science topics along with articles
...Instead of providing a single software package, the repository aggregates articles, tutorials, and examples covering many topics within the data science ecosystem. The materials address areas such as MLOps, data management, project organization, testing practices, visualization techniques, and productivity tools used by data scientists. Each topic often includes references to code repositories, demonstrations, and video tutorials that show how the tools can be applied in real projects. The repository is intended to help practitioners stay updated with current best practices and technologies in the field of data science. -
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mosaicml composer
Supercharge Your Model Training
composer is a deep learning training framework built on PyTorch and designed to make large-scale model training more efficient, scalable, and customizable. At the center of the project is a highly optimized Trainer abstraction that simplifies the management of training loops, parallelization, metrics, logging, and data loading. The framework is intended for modern workloads that may span anything from a single GPU to very large distributed training environments, which makes it suitable for both experimentation and production-scale development. ... -
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machine_learning_examples
A collection of machine learning examples and tutorials
machine_learning_examples is an open-source repository that provides a large collection of machine learning tutorials and practical code examples. The project aims to teach machine learning concepts through hands-on programming rather than purely theoretical explanations. It includes implementations of many machine learning algorithms and neural network architectures using Python and popular libraries such as TensorFlow and NumPy. The repository covers a wide range of topics including supervised learning, unsupervised learning, reinforcement learning, and natural language processing. ... -
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Coursera-ML-AndrewNg-Notes
Personal notes from Wu Enda's machine learning course
Coursera-ML-AndrewNg-Notes is an open-source repository that provides detailed study notes and explanations for Andrew Ng’s well-known machine learning course. The project aims to help students understand the mathematical concepts, algorithms, and intuition behind fundamental machine learning techniques taught in the course. It organizes the material into clear written summaries that accompany each lecture topic, including supervised learning, regression methods, neural networks, and optimization algorithms. ... -
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ML Retreat
Machine Learning Journal for Intermediate to Advanced Topics
ML Retreat is an open-source learning repository that serves as a structured journal documenting advanced topics in machine learning and artificial intelligence. The project compiles detailed notes, technical explanations, and curated resources that guide readers through complex concepts across modern AI research. Rather than functioning as a traditional tutorial series, the repository is organized as a learning journey that progressively explores increasingly advanced subjects. Topics include large language models, graph neural networks, mechanistic interpretability, transformer architectures, and emerging research areas such as quantum machine learning. ... -
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LLMSurvey
A Survey of Large Language Models
LLMSurvey is an open-source research repository that aggregates academic papers, resources, and references related to large language models. The project is closely associated with the academic survey titled “A Survey of Large Language Models,” which provides a comprehensive overview of the development, architecture, capabilities, and societal implications of modern LLMs. The repository organizes hundreds of research papers into thematic sections that reflect the main areas of LLM research, including model architectures, training strategies, evaluation benchmarks, alignment techniques, and downstream applications. ... -
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Machine Learning Engineering Open Book
Machine Learning Engineering Open Book
...The material spans the full ML lifecycle, from hardware selection and distributed training to inference optimization and debugging. Rather than focusing purely on theory, the project emphasizes engineering tradeoffs and production realities that often determine success at scale. It is continuously updated as a knowledge dump, making it especially valuable for engineers operating complex AI systems in the wild. -
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Artificial Intelligence for Beginners
12 Weeks, 24 Lessons, AI for All
...The curriculum is intentionally beginner-friendly while still exposing learners to widely used frameworks such as TensorFlow and PyTorch. It also supports many languages, making the material accessible to a global audience. Overall, the project functions as a complete self-paced learning pathway for students, educators, and developers who want a practical introduction to modern AI concepts. -
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Linux insides
A book-in-progress about the Linux kernel and its insides
Linux insides is an extensive open-source educational book project that explores the internal architecture and behavior of the Linux kernel. The repository contains a structured series of chapters that explain low-level topics such as booting, memory management, interrupts, system calls, and synchronization primitives. The project’s stated goal is to share knowledge about Linux kernel internals and related low-level concepts in an accessible narrative format. -
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OpenPlanter
Language-model investigation agent with a terminal UI
OpenPlanter is an open-source Python project focused on building an intelligent automated planting or gardening system powered by software control and data processing. The repository is designed to help developers and hobbyists create programmable plant management workflows that can monitor, schedule, and optimize growing conditions. It emphasizes automation and extensibility, allowing integration with sensors, environmental data, and control logic for smart cultivation setups. ... -
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Claude Code Plugins Directory
Official, Anthropic-managed directory of high quality Claude Plugins
Claude Code Plugins Directory repository provides a collection of plugins intended to extend Claude’s capabilities by turning the model into a specialized assistant tailored to specific workflows, teams, or organizational needs. These plugins define how Claude should access tools, retrieve data, and execute structured tasks so that outputs become more consistent and production-ready. The project emphasizes customizable automation by allowing developers to encode preferred workflows, domain knowledge, and operational rules directly into plugin configurations. It is built to work with Claude Cowork and Claude Code environments, enabling teams to standardize how AI assistance behaves across different use cases. By exposing slash commands and workflow logic, the repository helps organizations operationalize AI in real business contexts rather than relying on generic prompting. -
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PRML
PRML algorithms implemented in Python
PRML repository is a respected and well-maintained project that implements the foundational algorithms from the famous textbook Pattern Recognition and Machine Learning by Christopher M. Bishop, providing a practical and accessible Python reference for both students and professionals. Rather than just summarizing concepts, the repository includes working code that demonstrates linear regression and classification, kernel methods, neural networks, graphical models, mixture models with EM algorithms, approximate inference, and sequential data methods — all following the book’s structure and notation. ... -
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Claude Code Hooks Mastery
Master Claude Code Hooks
Claude Code Hooks Mastery is a trending community-centric GitHub repository aimed at helping developers master Claude Code hooks — customizable integration points that let users extend, automate, and augment workflows when using Claude Code, an agentic terminal coding assistant. Although the project itself doesn’t include a single coherent application, it functions as a curated collection of advanced hook examples, best practices, and coding patterns that show how to tailor Claude Code to specific use cases such as automated CI workflows, custom command triggers, and integrations with external tools. The repository is part of a larger ecosystem of Claude Code tooling that enables natural-language-driven coding tasks, and the hooks contained here help users go beyond default behaviors to solve real problems efficiently. -
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TurboDiffusion
100–200× Acceleration for Video Diffusion Models
...It achieves this by combining a suite of algorithmic and engineering optimizations, including attention acceleration techniques, efficient step distillation methods, and quantization strategies that reduce computational overhead. The project targets large video models and enables developers to run accelerated generation even on single high-end GPUs, making fast video synthesis more practical for research and creative workflows. TurboDiffusion is structured to integrate with existing diffusion model architectures and provides tools for experimenting with and benchmarking speed and quality trade-offs. -
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NitroGen
A Foundation Model for Generalist Gaming Agents
...This approach enables the model to control agents in different game genres and contexts, performing tasks that range from complex exploration and combat to fine-grained control in platformers, demonstrating adaptability across unseen environments. The project draws on MineDojo’s broader ecosystem for embodied AI, where multi-modal inputs and richly diverse benchmarks help push toward generalist AI capable of interactive decision making. -
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nanocode
Minimal Claude Code alternative. Single Python file, zero dependencies
...It includes a set of integrated tools such as read, write, edit, glob, grep, and bash that let the agent interact with the file system and shell commands directly from the terminal, and it keeps a conversation history with colored terminal output for readability. The project exemplifies how lightweight architectures can still support practical agent workflows without complex infrastructure, making it suitable for developers exploring agent frameworks or building custom coding assistants. -
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bu-agent-sdk
An agent is just a for-loop
The bu-agent-sdk from the Browser Use project is a minimalistic Python framework that defines an AI agent as a simple loop of tool calls, aiming to keep abstractions low so developers can build autonomous agents without unnecessary complexity. At its core, the agent loop repeatedly queries a large language model, interprets its output, and executes defined “tools” — functions annotated with task names — to perform actions, allowing the agent to complete tasks like arithmetic, decision-making, or domain-specific work. ... -
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Manim Skills Repository
Agent skills for Manim to create 3Blue1Brown style animations
...It supplies templates, best-practice patterns, and example scenes that help users quickly get started with both Manim Community Edition and the older ManimGL framework, allowing for expressive mathematical and conceptual animations without reinventing the wheel. The project aims to wrap common animation logic into structured skills that can be invoked programmatically, reducing boilerplate and allowing creators to focus on creative content rather than low-level animation setup. With clear installation instructions and a collection of test cases, it’s approachable for developers comfortable with Python and interested in educational or technical visualization. -
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OpenMLSys-ZH
Machine Learning Systems: Design and Implementation
This repository is the Chinese translation (or localization) of the OpenMLSys project documentation. Its aim is to make the technical content, tutorials, architecture descriptions, and user guides of the OpenMLSys system more accessible to Chinese-speaking users. The repo mirrors the structure of the original OpenMLSys docs: sections on system design, API references, deployment instructions, module overviews, and example workflows. -
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AI Hedge Fund
An AI Hedge Fund Team
...Its structure is educational: intended more as a proof-of-concept than a ready-to-use financial product, giving learners insight into the mechanics of quantitative finance automation. The project underlines AI’s potential in investment strategies but also carries disclaimers that it is for research and not financial advice. The implementation is designed so developers can study the pipeline end-to-end: from data ingestion through modeling to simulated portfolio management. -
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OpenLIT
OpenLIT is an open-source LLM Observability tool
...Whether you're working with popular LLM providers such as OpenAI and HuggingFace, or leveraging vector databases like ChromaDB, OpenLIT ensures your applications are monitored seamlessly, providing critical insights including GPU performance stats for self-hosted LLMs to improve performance and reliability. This project proudly follows the Semantic Conventions of the OpenTelemetry community, consistently updating to align with the latest standards in observability. -
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Python Progressbar
Progressbar 2 - A progress bar for Python 2 and Python 3
A text progress bar is typically used to display the progress of a long-running operation, providing a visual cue that processing is underway. The progressbar is based on the old Python progressbar package that was published on the now-defunct Google Code. Since that project was completely abandoned by its developer and the developer did not respond to my email, I decided to fork the package. This package is still backward compatible with the original progressbar package so you can safely use it as a drop-in replacement for existing projects. The ProgressBar class manages the current progress, and the format of the line is given by a number of widgets. ... -
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Kale
Kubeflow’s superfood for Data Scientists
KALE (Kubeflow Automated pipeLines Engine) is a project that aims at simplifying the Data Science experience of deploying Kubeflow Pipelines workflows. Kubeflow is a great platform for orchestrating complex workflows on top Kubernetes and Kubeflow Pipeline provides the mean to create reusable components that can be executed as part of workflows. The self-service nature of Kubeflow make it extremely appealing for Data Science use, at it provides an easy access to advanced distributed jobs orchestration, re-usability of components, Jupyter Notebooks, rich UIs and more. ...
