Search Results for "web based"
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Showing 6 open source projects for "web based"
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Full-stack observability with actually useful AI | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
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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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RStudio
RStudio is an integrated development environment (IDE) for R
RStudio is a powerful, full-featured integrated development environment (IDE) tailored primarily for the R programming language but increasingly supportive of other languages like Python and Julia. It brings together console, editor, plotting, workspace, history, and file-management panes into a unified interface, helping data scientists, statisticians, and analysts to work more productively. The IDE is cross-platform: there are desktop versions for Windows, macOS and Linux, as well as a... -
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Quadratic
Data science spreadsheet with Python & SQL
Quadratic enables your team to work together on data analysis to deliver better results, faster. You already know how to use a spreadsheet, but you’ve never had this much power before. Quadratic is a Web-based spreadsheet application that runs in the browser and as a native app (via Electron). Our goal is to build a spreadsheet that enables you to pull your data from its source (SaaS, Database, CSV, API, etc) and then work with that data using the most popular data science tools today (Python, Pandas, SQL, JS, Excel Formulas, etc). ... -
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Catbird Linux
Linux for content creation, web scraping, coding, and data analysis.
Catbird Linux is a USB pluggable Live Linux operating system built for media creation, web scraping, and software coding. It is the daily driver you want for retrieving data, making videos or podcasts, and making software tools to automate the repetitive tasks. It is ready for work in Python, Lua, and Go languages, with numerous packages for web scraping or downloading data via API calls. Using Catbird Linux, it is possible to accomplish in depth stock market analysis, track weather... -
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ML workspace
All-in-one web-based IDE specialized for machine learning
All-in-one web-based development environment for machine learning. The ML workspace is an all-in-one web-based IDE specialized for machine learning and data science. It is simple to deploy and gets you started within minutes to productively built ML solutions on your own machines. This workspace is the ultimate tool for developers preloaded with a variety of popular data science libraries (e.g., Tensorflow, PyTorch, Keras, Sklearn) and dev tools (e.g., Jupyter, VS Code, Tensorboard) perfectly configured, optimized, and integrated. ... -
Try Google Cloud Risk-Free With $300 in CreditUse your credit across every product. Compute, storage, AI, analytics. When it runs out, 20+ products stay free. You only pay when you choose to.
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Spark Notebook
Interactive and Reactive Data Science using Scala and Spark
Spark Notebook is an interactive web-based computational notebook designed to make working with Apache Spark more productive, exploratory, and expressive. It allows developers, data scientists, and analysts to write, run, and visualize Spark code in cells that support multiple languages such as Scala, Python, and SQL, all within the same notebook. Users can interleave runnable code, rich text markup, visualizations, equations, and results, enabling reproducible research and exploratory data analysis workflows. ... -
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slycat
Web-based data science analysis and visualization platform.
This is Slycat - a web-based data science analysis and visualization platform, created at Sandia National Laboratories. The goal of the Slycat project is to develop processes, tools and techniques to support data science, particularly analysis of large, high-dimensional data.
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