Search Results for "analysis" - Page 7
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Showing 1227 open source projects for "analysis"
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1
DocETL
A system for agentic LLM-powered data processing and ETL
...The platform allows developers and researchers to construct structured workflows that extract, transform, and organize information from sources such as reports, transcripts, legal documents, and other text-heavy data. Instead of relying on single prompts or ad-hoc scripts, DocETL provides a declarative pipeline framework that breaks complex document analysis tasks into manageable operations that can be optimized and orchestrated automatically. Pipelines are typically defined using a low-code YAML interface, giving users full control over prompts and processing steps while still simplifying workflow creation. -
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JS Analyzer
Burp Suite extension for JavaScript static analysis
JS Analyzer is a powerful static analysis tool implemented as a Burp Suite extension that helps security researchers and web developers automatically uncover important artifacts in JavaScript files during web application testing. It parses JavaScript responses intercepted by Burp Suite and intelligently extracts API endpoints, full URLs (including cloud storage links), secrets like API keys or tokens, and email addresses while filtering out noise from irrelevant code patterns. ... -
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TrendRadar
AI-driven public opinion trend monitor with multi-platform aggregation
TrendRadar is an AI-powered trend and hotspot tracking system that aggregates information from dozens of news, social, and content platforms to help users cut through information overload and focus on what matters. It automatically crawls and monitors trends across 30+ sources with smart filtering, keyword triggers, sentiment analysis, and natural language summarization to give actionable insights. The tool supports multiple alert modes—such as daily summaries, incremental change monitoring, and current rankings—and can push notifications through messaging platforms like Telegram, Slack, WeChat, DingTalk, and email. Users can deploy it quickly via Python and GitHub Actions, and it also supports RSS feeds and Docker deployment for flexible integration. ... -
4
Napkin
An Infinitely Large Napkin
...It is not a polished textbook full of full proofs; rather it offers clean definitions, theorem statements, intuitive motivations, and informal sketches of why things work, with the goal of building conceptual understanding. The coverage spans undergraduate and early graduate topics, designed to show how different areas of math fit together—linear algebra, analysis, topology, number theory, and more—without going deeply into every subtopic. Because it is written in LaTeX (with supporting Asymptote or other tools), readers can compile their own version, and the repository integrates diagrams, flowcharts, and supplementary files. -
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5
Perf Book
The book "Performance Analysis and Tuning on Modern CPU"
This project is a practical guide to performance analysis and tuning on modern CPUs, bridging microarchitecture details with hands-on profiling. It explains how caches, TLBs, prefetchers, branch predictors, and out-of-order execution influence real program speed, then connects those concepts to concrete optimization strategies. Readers learn how to design trustworthy benchmarks, avoid measurement traps (warmup, turbo, frequency scaling), and interpret hardware performance counters. ... -
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SublimeLinter-eslint
This linter plugin for SublimeLinter provides an interface to ESLint
This linter plugin for SublimeLinter provides an interface to ESLint. It will be used with "JavaScript" files, but since eslint is pluggable, it can actually lint a variety of other files as well. SublimeLinter will detect some installed local plugins, and thus it should work automatically for e.g. .vue or .ts files. If it works on the command line, there is a chance it works in Sublime without further ado. Make sure the plugins are installed locally colocated to eslint itself. T.i.,... -
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TensorFlow Probability
Probabilistic reasoning and statistical analysis in TensorFlow
TensorFlow Probability is a library for probabilistic reasoning and statistical analysis. TensorFlow Probability (TFP) is a Python library built on TensorFlow that makes it easy to combine probabilistic models and deep learning on modern hardware (TPU, GPU). It's for data scientists, statisticians, ML researchers, and practitioners who want to encode domain knowledge to understand data and make predictions. Since TFP inherits the benefits of TensorFlow, you can build, fit, and deploy a model using a single language throughout the lifecycle of model exploration and production. ... -
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Xteam
All-in-one command-line toolkit for security testing and OSINT tools
Xteam is a command-line security toolkit designed to provide multiple penetration testing and information-gathering utilities in a single interface. It combines several modules and external tools to help users perform security research tasks related to mobile devices, wireless networks, and online services. It acts as a centralized launcher that integrates scripts and third-party tools, allowing users to access different testing functions through a menu-based command line workflow. Xteam... -
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AutoClip
AI-powered video clipping and highlight generation
AutoClip is an open-source, AI-powered video processing system designed to automate the extraction of “highlight” segments from full-length videos — ideal for creators who want to generate bite-sized clips, compilations, or highlight reels without manually sifting through hours of footage. The system supports downloading videos from major platforms (e.g. YouTube, Bilibili), or accepting local uploads, and then applies AI analysis to identify segments worth clipping based on content (e.g. high energy moments, speech, or other heuristics). Once highlights are identified, AutoClip can automatically cut those segments and optionally assemble them into a compilation, thus greatly reducing manual video editing effort. It uses a modern web application stack with a front end (React + TypeScript) for user interaction and a back end that handles downloading, processing, clipping, and queue management, allowing real-time progress feedback and easy deployment, e.g. via Docker. -
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Toutatis
Extract public Instagram account information from usernames
...The utility is implemented in Python and runs through a simple command-line interface, making it easy to integrate into OSINT workflows and automation scripts. Toutatis is commonly used in open source intelligence investigations, research tasks, and security analysis that involve collecting publicly available social media data. -
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Fingerprint Pro Server Python SDK
Python SDK for Fingerprint Pro Server API
Fingerprint Pro Server API allows you to get information about visitors and about individual events in a server environment. It can be used for data exports, decision-making, and data analysis scenarios. Server API is intended for server-side usage, it's not intended to be used from the client side, whether it's a browser or a mobile device. -
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finvizfinance
Finviz analysis python library
finvizfinance is a package that collects financial information from FinViz website. Stock charts, fundamental & technical information, insider information and stock news. Forex charts and performance. Crypto charts and performance. Screener and Group provide data frames for comparing stocks according to different filters and trading signals. Getting information (fundament, description, outer rating, stock news, inside trader) of an individual stock. -
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GeoAI
GeoAI: Artificial Intelligence for Geospatial Data
GeoAI is a comprehensive open-source Python package designed to integrate artificial intelligence techniques with geospatial data analysis, enabling users to perform advanced geographic modeling and visualization tasks with ease. It provides a unified framework that combines machine learning libraries such as PyTorch and Transformers with geospatial tools, allowing users to process satellite imagery, aerial photos, and vector datasets in a streamlined workflow. The platform supports a wide range of tasks including image classification, object detection, segmentation, and change detection, making it suitable for applications in environmental monitoring, urban planning, and disaster response. ... -
14
OpenRecall
OpenRecall is a fully open-source, privacy-first alternative
OpenRecall is an open-source, privacy-first system designed to capture, index, and make searchable a user’s entire digital activity history, effectively acting as a personal memory layer for computing environments. It works by taking periodic screenshots of a user’s screen and applying local AI processing, including OCR and semantic analysis, to extract and structure information from both text and images. This data is then indexed into a searchable database, allowing users to retrieve past information quickly using natural language queries. Unlike proprietary alternatives, OpenRecall operates entirely locally, ensuring that all captured data remains on the user’s device and is never transmitted to external servers. ... -
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Docling
Get your documents ready for gen AI
...The project focuses on converting and parsing many document formats into a unified structured representation that downstream systems can easily consume. It supports advanced PDF understanding, including layout detection, table extraction, and reading order analysis, enabling high-fidelity document intelligence pipelines. Docling is designed to run efficiently on commodity hardware and can be used both as a Python API and a command-line tool. Its modular architecture allows developers to extend functionality and integrate specialized models for tasks such as OCR and audio transcription. Overall, Docling serves as a comprehensive preprocessing layer for AI applications that require reliable, structured access to complex document data. -
16
MemU
MemU is an open-source memory framework for AI companions
...Full proprietary features, commercial usage rights, and white-labeling options for your enterprise needs. SSO/RBAC integration and a dedicated algorithm team for scenario-specific optimization. User behavior analysis, real-time monitoring, and automated agent optimization tools. 24/7 dedicated support team, custom SLAs, and professional implementation services. -
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Droidrun
Powerful framework for controlling Android and iOS devices
Droidrun is a native mobile agent platform that gives users natural-language control over real Android devices to automate any mobile app workflow, from logins and bookings to purchases and data extraction, including access to mobile-only content behind app logins, rate limits, or platform restrictions. Its cloud offering lets users spin up agents in seconds with preinstalled apps, run tasks in parallel across multiple devices, and compose complex, multi-step conditional workflows using... -
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fklearn
Functional Machine Learning
fklearn uses functional programming principles to make it easier to solve real problems with Machine Learning. -
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ContextGem
ContextGem: Effortless LLM extraction from documents
...It provides a flexible, intuitive API that minimizes boilerplate code, enabling developers to build complex extraction workflows efficiently. ContextGem supports various document formats and integrates with multiple LLM providers, making it a versatile tool for tasks like contract analysis, anomaly detection, and information retrieval. -
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E2B Cookbook
Examples of using E2B
...The repository acts as a practical learning resource for developers who want to integrate AI agents with secure cloud execution environments that allow large language models to run code and interact with tools. The examples illustrate how developers can build AI workflows capable of performing tasks such as data analysis, code execution, and application generation inside isolated sandbox environments. E2B itself provides secure Linux-based sandboxes that enable AI systems to safely run generated code and interact with real computing resources without compromising the host environment. The cookbook organizes examples across multiple frameworks and model providers, allowing developers to experiment with integrations involving models from OpenAI, Anthropic, and other ecosystems. -
21
OWASP Maryam
Modular OSINT framework for automated open-source intelligence gatheri
...Maryam helps security researchers and analysts streamline routine data-gathering tasks that typically involve searching multiple sources such as Google, Bing, or other online platforms. Maryam organizes its functionality into several modules that focus on different aspects of intelligence gathering, including footprint analysis, OSINT data extraction, and general search operations. -
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Pandas Profiling
Create HTML profiling reports from pandas DataFrame objects
pandas-profiling generates profile reports from a pandas DataFrame. The pandas df.describe() function is handy yet a little basic for exploratory data analysis. pandas-profiling extends pandas DataFrame with df.profile_report(), which automatically generates a standardized univariate and multivariate report for data understanding. High correlation warnings, based on different correlation metrics (Spearman, Pearson, Kendall, Cramér’s V, Phik). Most common categories (uppercase, lowercase, separator), scripts (Latin, Cyrillic) and blocks (ASCII, Cyrilic). ... -
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wemake-python-styleguide
The strictest and most opinionated python linter ever!
Welcome to the strictest and most opinionated Python linter ever. wemake-python-styleguide is actually a flake8 plugin with some other plugins as dependencies. Ensures consistency - no matter who works on it, the end product will always be the same dependable code. Helps avoid potential bugs - strict rules make sure that you don't make common mistakes. Efficient code reviews - each piece of code has a similar familiar style and syntax. If it passes all the checks, there's little left to... -
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Super-Linter
Combination of multiple linters to install as a GitHub Action
This repository is for the GitHub Action to run a Super-Linter. It is a simple combination of various linters, written in bash, to help validate your source code. The super-linter finds issues and reports them to the console output. Fixes are suggested in the console output but not automatically fixed, and a status check will show up as failed on the pull request. The design of the Super-Linter is currently to allow linting to occur in GitHub Actions as a part of continuous integration... -
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Claude Scientific Skills
A set of ready to use Agent Skills for research, science, engineering
Claude Scientific Skills is a large open source collection of ready-to-use scientific capabilities that extend AI coding agents into full research assistants. The project provides more than 170 curated skills covering domains such as genomics, drug discovery, medical imaging, physics, and advanced data analysis. Each skill bundles documentation, examples, and tool integrations so agents can reliably execute complex multi-step scientific workflows. The framework follows the open Agent Skills standard and works with multiple AI development environments including Claude Code, Cursor, and Codex. Its primary goal is to reduce the friction of scientific computing by giving AI agents structured access to specialized libraries, databases, and research pipelines. ...
