Search Results for "g-code"
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Showing 143 open source projects for "g-code"
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Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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Streamline Azure Security with Palo Alto Networks VM-SeriesImprove your security posture and reduce incident response time. Use the VM-Series to natively analyze Azure traffic and dynamically drive policy updates based on workload changes.
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Modin
Scale your Pandas workflows by changing a single line of code
Scale your pandas workflow by changing a single line of code. Modin uses Ray, Dask or Unidist to provide an effortless way to speed up your pandas notebooks, scripts, and libraries. Unlike other distributed DataFrame libraries, Modin provides seamless integration and compatibility with existing pandas code. Even using the DataFrame constructor is identical. It is not necessary to know in advance the available hardware resources in order to use Modin. -
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Mage.ai
Build, run, and manage data pipelines for integrating data
...Have you met anyone who said they loved developing in Airflow? That’s why we designed an easy developer experience that you’ll enjoy. Each step in your pipeline is a standalone file containing modular code that’s reusable and testable with data validations. No more DAGs with spaghetti code. Start developing locally with a single command or launch a dev environment in your cloud using Terraform. Write code in Python, SQL, or R in the same data pipeline for ultimate flexibility. -
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Dash
Build beautiful web-based analytic apps, no JavaScript required
...Built on top of Plotly.js, React and Flask, Dash easily achieves what an entire team of designers and engineers normally would. It ties modern UI controls and displays such as dropdown menus, sliders and graphs directly to your analytical Python code, and creates exceptional, interactive analytics apps. Dash apps are very lightweight, requiring only a limited number of lines of Python or R code; and every aesthetic element can be customized and rendered in the web. It’s also not just for dashboards. You have full control over the look and feel of your apps, so you can style them to look any way you want. -
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ClearML
Streamline your ML workflow
ClearML is an open source platform that automates and simplifies developing and managing machine learning solutions for thousands of data science teams all over the world. It is designed as an end-to-end MLOps suite allowing you to focus on developing your ML code & automation, while ClearML ensures your work is reproducible and scalable. The ClearML Python Package for integrating ClearML into your existing scripts by adding just two lines of code, and optionally extending your experiments and other workflows with ClearML powerful and versatile set of classes and methods. The ClearML Server storing experiment, model, and workflow data, and supports the Web UI experiment manager, and ML-Ops automation for reproducibility and tuning. ... -
Gemini 3 and 200+ AI Models on One PlatformBuild, govern, and optimize agents and models with Gemini Enterprise Agent Platform.
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miepython
Mie scattering of light by perfect spheres
miepython is a pure Python module to calculate light scattering for non-absorbing, partially-absorbing, or perfectly-conducting spheres. Mie theory is used, following the procedure described by Wiscombe. This code has been validated against his results. This code provides functions for calculating the extinction efficiency, scattering efficiency, backscattering, and scattering asymmetry. Moreover, a set of angles can be given to calculate the scattering for a sphere at each of those angles. -
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Positron
Positron, a next-generation data science IDE
...The IDE supports notebook and script workflows, integration of data-app frameworks (such as Shiny, Streamlit, Dash), database and cloud connections, and built-in AI-assisted capabilities to help write code, explore data, and build models. -
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Matplotlib
matplotlib: plotting with Python
Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. Matplotlib makes easy things easy and hard things possible. Matplotlib ships with several add-on toolkits, including 3D plotting with mplot3d, axes helpers in axes_grid1 and axis helpers in axisartist. A large number of third party packages extend and build on Matplotlib functionality, including several higher-level plotting interfaces (seaborn, HoloViews, ggplot, ...), and a... -
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geemap
A Python package for interactive geospaital analysis and visualization
...GEE provides both JavaScript and Python APIs for making computational requests to the Earth Engine servers. Compared with the comprehensive documentation and interactive IDE (i.e., GEE JavaScript Code Editor) of the GEE JavaScript API, the GEE Python API has relatively little documentation and limited functionality for visualizing results interactively. The geemap Python package was created to fill this gap. -
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Apache Airflow
Programmatically author, schedule, and monitor workflows
Apache Airflow is a community-created platform for programmatically authoring, scheduling, and monitoring workflows. It’s much easier to do all these things when workloads are defined as code. They become more versionable, testable, maintainable and collaborative. With Airflow you can author workflows as directed acyclic graphs (DAGs) of tasks. This means that your tasks are executed on an array of workers while following the specified dependencies. And with rich command line utilities in place, performing complex surgeries on DAGs is simple and straightforward. ... -
Earn up to 16% annual interest with Nexo.Generate interest, access liquidity without selling, and execute trades seamlessly. All in one platform. Geographic restrictions, eligibility, and terms apply.
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QuantDinger
AI-driven, local-first quantitative trading platform for research
...QuantDinger also incorporates optional AI features via external APIs, assisting in tasks like strategy ideation or interpreting market indicators, but strategy logic remains inspectable and transparent in code. -
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Mercury
Convert Python notebook to web app and share with non-technical users
...You define interactive widgets for your notebook with the YAML header. Your users can change the widgets values, execute the notebook and save result (as PDF or html file). You can hide your code to not scare your (non-coding) collaborators. Easily deploy to any server. Mercury is dual-licensed. Looking for dedicated support, a commercial-friendly license, and more features? The Mercury Pro is for you. -
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Cookiecutter Data Science
Project structure for doing and sharing data science work
...When we think about data analysis, we often think just about the resulting reports, insights, or visualizations. While these end products are generally the main event, it's easy to focus on making the products look nice and ignore the quality of the code that generates them. Because these end products are created programmatically, code quality is still important! And we're not talking about bikeshedding the indentation aesthetics or pedantic formatting standards, ultimately, data science code quality is about correctness and reproducibility. It's no secret that good analyses are often the result of very scattershot and serendipitous explorations. ... -
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CKAN
CKAN is an open-source DMS for powering data hubs
CKAN is the world’s leading open-source data portal platform. CKAN makes it easy to publish, share and work with data. It's a data management system that provides a powerful platform for cataloging, storing and accessing datasets with a rich front-end, full API (for both data and catalog), visualization tools and more.CKAN is used by national and regional government organizations throughout the European Union, the Americas, Asia, and Oceania to power a variety of official and community data... -
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Dagster
An orchestration platform for the development, production
Dagster is an orchestration platform for the development, production, and observation of data assets. Dagster as a productivity platform: With Dagster, you can focus on running tasks, or you can identify the key assets you need to create using a declarative approach. Embrace CI/CD best practices from the get-go: build reusable components, spot data quality issues, and flag bugs early. Dagster as a robust orchestration engine: Put your pipelines into production with a robust... -
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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. 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. ... -
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H2O Wave
Realtime Web Apps and Dashboards for Python and R
...Broadcast live information, visualizations, and graphics using Wave's low-latency real-time server. Instant control over every connected web browser using a simple and intuitive programming model. Preview your app live as you code. Dramatically reduce the time and effort to build web apps. Easily share your apps with end-users, get feedback, improve and iterate. ~10MB static executables for Linux, Windows, OSX, BSD, Solaris on AMD64, 386, ARM, PPC. Run it on a RPi Zero for great good! -
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NautilusTrader
A high-performance algorithmic trading platform
NautilusTrader is an open-source, high-performance, production-grade algorithmic trading platform, provides quantitative traders with the ability to backtest portfolios of automated trading strategies on historical data with an event-driven engine, and also deploy those same strategies live, with no code changes. The platform is 'AI-first', designed to develop and deploy algorithmic trading strategies within a highly performant and robust Python native environment. This helps to address the parity challenge of keeping the Python research/backtest environment, consistent with the production live trading environment. NautilusTraders design, architecture and implementation philosophy holds software correctness and safety at the highest level, with the aim of supporting Python native, mission-critical, trading system backtesting and live deployment workloads. -
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marimo
A reactive notebook for Python
marimo is an open-source reactive notebook for Python, reproducible, git-friendly, executable as a script, and shareable as an app. marimo notebooks are reproducible, extremely interactive, designed for collaboration (git-friendly!), deployable as scripts or apps, and fit for modern Pythonista. Run one cell and marimo reacts by automatically running affected cells, eliminating the error-prone chore of managing the notebook state. marimo's reactive UI elements, like data frame GUIs and plots,... -
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NVIDIA Merlin
Library providing end-to-end GPU-accelerated recommender systems
...Scale large deep learning recommender models by distributing large embedding tables that exceed available GPU and CPU memory. Deploy data transformations and trained models to production with only a few lines of code. -
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AIQuant
AI-powered platform for quantitative trading
...Stock trading strategies: large models, factor mining, traditional strategies, machine learning, deep learning, reinforcement learning, graph networks, high-frequency trading, etc. Resource summary: network-wide resource summary, practical cases, paper interpretation, and code implementation. -
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Yahoo! Finance market data downloader
Yahoo! Finance market data downloader
...finance. yfinance aimed to offer a temporary fix to the problem by scraping the data from Yahoo! Finance and returning a the data in the same format as pandas_datareader's get_data_yahoo(), thus keeping the code changes in existing software to a minimum. The latest version of yfinance is a complete re-write of the libray, offering a reliable method of downloading historical market data from Yahoo! Finance, up to 1 minute granularity, with a more Pythonic way. The Ticker() module allows you get market and metadata for security, using a Pythonic way. -
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Tally
Let agents classify your bank transactions
Tally is an open-source, AI-assisted tool designed to automate the classification of personal financial transactions, helping users turn raw bank data into meaningful categories without manual tagging. At its core, Tally pairs a local rule engine with large language models so that an AI assistant (like Claude Code, Copilot, or any CLI agent) interprets, suggests, and categorizes expenses, savings, subscriptions, and income events based on your own rules and behavior. It generates human-readable reports and can produce HTML, JSON, or Markdown outputs to suit dashboards or personal finance workflows. The project emphasizes transparency, allowing users to see why a particular transaction was classified a certain way and to refine rules over time. ... -
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CleanVision
Automatically find issues in image datasets
...This data-centric AI package is a quick first step for any computer vision project to find problems in the dataset, which you want to address before applying machine learning. CleanVision is super simple -- run the same couple lines of Python code to audit any image dataset! The quality of machine learning models hinges on the quality of the data used to train them, but it is hard to manually identify all of the low-quality data in a big dataset. CleanVision helps you automatically identify common types of data issues lurking in image datasets. This package currently detects issues in the raw images themselves, making it a useful tool for any computer vision task such as: classification, segmentation, object detection, pose estimation, keypoint detection, generative modeling, etc. -
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Dask
Parallel computing with task scheduling
Dask is a Python library for parallel and distributed computing, designed to scale analytics workloads from single machines to large clusters. It integrates with familiar tools like NumPy, Pandas, and scikit-learn while enabling execution across cores or nodes with minimal code changes. Dask excels at handling large datasets that don’t fit into memory and is widely used in data science, machine learning, and big data pipelines. -
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JS Analyzer
Burp Suite extension for JavaScript static analysis
...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. The extension is designed to reduce manual effort when analyzing large or obfuscated JavaScript assets, helping testers find security vulnerabilities and sensitive information faster and more reliably. It also includes UI features such as live search, result filtering, and the ability to export findings in JSON format for further processing. ...
