Search Results for "data science"
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Showing 4562 open source projects for "data science"
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SKUDONET ADC, operates at the application layer, efficiently distributing network load and application load across multiple servers. This not only enhances the performance of your application but also ensures that your web servers can handle more traffic seamlessly.
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HubSpot is an AI-powered customer platform with all the software, integrations, and resources you need to connect your marketing, sales, and customer service. HubSpot's connected platform enables you to grow your business faster by focusing on what matters most: your customers.
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AWESOME DATA SCIENCE
Awesome Data Science repository to learn and apply for real world
An open source Data Science repository to learn and apply towards solving real world problems. This is a shortcut path to start studying Data Science. Just follow the steps to answer the questions, "What is Data Science and what should I study to learn Data Science?" Data Science is one of the hottest topics on the Computer and Internet farmland nowadays. People have gathered data from applications and systems until today and now is the time to analyze them. The next steps are producing... -
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Cookiecutter Data Science
Project structure for doing and sharing data science work
A logical, reasonably standardized, but flexible 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... -
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Julia Data Science
Book on Julia for Data Science
This is an open source and open access book on how to do Data Science using Julia. Our target audience are researchers from all fields of applied sciences. Of course, we hope to be useful for industry too. You can navigate through the pages of the ebook by using the arrow keys (left/right) on your keyboard. -
Docubee is an intelligent contract automation platform that allows you to quickly and painlessly generate, manage, share, and sign contracts. Featuring powerful conditional logic-based workflows, generative AI technology, and an easily adaptable interface, Docubee makes it easy to automate your most complex contracts and agreements.
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AWS Step Functions Data Science SDK
For building machine learning (ML) workflows and pipelines on AWS
The AWS Step Functions Data Science SDK is an open-source library that allows data scientists to easily create workflows that process and publish machine learning models using Amazon SageMaker and AWS Step Functions. You can create machine learning workflows in Python that orchestrate AWS infrastructure at scale, without having to provision and integrate the AWS services separately. The best way to quickly review how the AWS Step Functions Data Science SDK works is to review the related example... -
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ggplot2
An implementation of the Grammar of Graphics in R
... for plotting. In most cases using ggplot2 starts with supplying a dataset and aesthetic mapping (with aes()); adding on layers (like geom_point() or geom_histogram()), scales (like scale_colour_brewer()), and faceting specifications (like facet_wrap()); and finally, coordinating systems. ggplot2 has a rich ecosystem of community-maintained extensions for those looking for more innovation. ggplot2 is a part of the tidyverse, an ecosystem of R packages designed for data science. -
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Nuclio
High-Performance Serverless event and data processing platform
Nuclio is an open source and managed serverless platform used to minimize development and maintenance overhead and automate the deployment of data-science-based applications. Real-time performance running up to 400,000 function invocations per second. Portable across low laptops, edge, on-prem and multi-cloud deployments. The first serverless platform supporting GPUs for optimized utilization and sharing. Automated deployment to production in a few clicks from Jupyter notebook. Deploy one... -
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Lua
The Lua development repository, as seen by the Lua team
Lua is a powerful, efficient, lightweight, embeddable scripting language. It supports procedural programming, object-oriented programming, functional programming, data-driven programming, and data description. Lua combines simple procedural syntax with powerful data description constructs based on associative arrays and extensible semantics. Lua is dynamically typed, runs by interpreting bytecode with a register-based virtual machine, and has automatic memory management with incremental garbage... -
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OpenRefine
A free, open source, powerful tool for working with messy data
..., then that is the only time the data will be shared outside of your computer. OpenRefine is available in over 15 languages, is cross-platform and part of the Code for Science & Society. -
Email is the backbone of your customer engagement. The Twilio SendGrid Email API is the email service trusted by developers and marketers for time-savings, scalability, and delivery expertise. Our flexible Email API and proprietary Mail Transfer Agent (MTA), intuitive console, powerful features, and email experts make it easy to ensure all your email gets delivered in seconds and without interruption.
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Gradio
Create UIs for your machine learning model in Python in 3 minutes
... them interact with the model on your computer remotely from their own devices. Once you've created an interface, you can permanently host it on Hugging Face. Hugging Face Spaces will host the interface on its servers and provide you with a link you can share. One of the best ways to share your machine learning model, API, or data science workflow with others is to create an interactive demo that allows your users or colleagues to try out the demo in their browsers. -
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Milvus
Vector database for scalable similarity search and AI applications
... vector datasets. Rich APIs designed for data science workflows. Consistent user experience across laptop, local cluster, and cloud. Embed real-time search and analytics into virtually any application. Milvus’ built-in replication and failover/failback features ensure data and applications can maintain business continuity in the event of a disruption. Component-level scalability makes it possible to scale up and down on demand. -
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coronavirus
The coronavirus dataset
The coronavirus package gives a tidy format dataset of the 2019 Novel Coronavirus COVID-19 (2019-nCoV) epidemic. Relevant and updated information about the virus, such as summary of new cases by country and total number of cases by region can be retrieved from this package. The raw data is pulled and arranged by the Johns Hopkins University Center for Systems Science and Engineering, which is gathered from various leading sources including the World Health Organization, China CDC, US CDC... -
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Kedro
A Python framework for creating reproducible, maintainable code
Kedro is an open sourced Python framework for creating maintainable and modular data science code. Provides the scaffolding to build more complex data and machine-learning pipelines. In addition, there's a focus on spending less time on the tedious "plumbing" required to maintain data science code; this means that you have more time to solve new problems. Standardises team workflows; the modular structure of Kedro facilitates a higher level of collaboration when teams solve problems together... -
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PSLab Android App
PSLab Android App
Repository for the PSLab Android App for performing experiments with the Pocket Science Lab open-hardware platform. This repository holds the Android App for performing experiments with PSLab. PSLab is a tiny pocket science lab that provides an array of equipment for doing science and engineering experiments. It can function like an oscilloscope, waveform generator, frequency counter, programmable voltage and current source and also as a data logger. PSLab is a tiny pocket science lab... -
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Synapse Machine Learning
Simple and distributed Machine Learning
SynapseML (previously MMLSpark) is an open source library to simplify the creation of scalable machine learning pipelines. SynapseML builds on Apache Spark and SparkML to enable new kinds of machine learning, analytics, and model deployment workflows. SynapseML adds many deep learning and data science tools to the Spark ecosystem, including seamless integration of Spark Machine Learning pipelines with the Open Neural Network Exchange (ONNX), LightGBM, The Cognitive Services, Vowpal Wabbit... -
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DataSophon
The next generation of cloud-native big data management expert
Aiming at quickly deploying, managing, monitoring and automating the operation and maintenance of Big Data service components and nodes, helping you quickly build stable, efficient Big Data cluster services. The Three-Body Problem, a Hugo Award-winning work of the world's highest science fiction literature, is known for its stunning "hard science fiction" style, and its author Liu Cixin is credited with "single-handedly raising Chinese science fiction to a world-class level". As a very... -
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CML
Continuous Machine Learning | CI/CD for ML
Continuous Machine Learning (CML) is an open-source CLI tool for implementing continuous integration & delivery (CI/CD) with a focus on MLOps. Use it to automate development workflows, including machine provisioning, model training and evaluation, comparing ML experiments across project history, and monitoring changing datasets. CML can help train and evaluate models, and then generate a visual report with results and metrics, automatically on every pull request. -
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XGBoost
Scalable and Flexible Gradient Boosting
XGBoost is an optimized distributed gradient boosting library, designed to be scalable, flexible, portable and highly efficient. It supports regression, classification, ranking and user defined objectives, and runs on all major operating systems and cloud platforms. XGBoost works by implementing machine learning algorithms under the Gradient Boosting framework. It also offers parallel tree boosting (GBDT, GBRT or GBM) that can quickly and accurately solve many data science problems. XGBoost... -
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DearPyGui
Graphical User Interface Toolkit for Python with minimal dependencies
... and demanding graphical interfaces. DPG offers a solid framework for developing scientific, engineering, gaming, data science and other applications that require fast and interactive interfaces. The Tutorials will provide a great overview and links to each topic in the API Reference for more detailed reading. Complete theme and style control. GPU-based rendering and efficient C/C++ code. -
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TensorFlow.NET
.NET Standard bindings for Google's TensorFlow for developing models
TensorFlow.NET (TF.NET) provides a .NET Standard binding for TensorFlow. It aims to implement the complete Tensorflow API in C# which allows .NET developers to develop, train and deploy Machine Learning models with the cross-platform .NET Standard framework. TensorFlow.NET has built-in Keras high-level interface and is released as an independent package TensorFlow.Keras. SciSharp STACK's mission is to bring popular data science technology into the .NET world and to provide .NET developers... -
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Metaflow
A framework for real-life data science
Metaflow is a human-friendly Python library that helps scientists and engineers build and manage real-life data science projects. Metaflow was originally developed at Netflix to boost productivity of data scientists who work on a wide variety of projects from classical statistics to state-of-the-art deep learning. -
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Great Expectations
Always know what to expect from your data
Great Expectations helps data teams eliminate pipeline debt, through data testing, documentation, and profiling. Software developers have long known that testing and documentation are essential for managing complex codebases. Great Expectations brings the same confidence, integrity, and acceleration to data science and data engineering teams. Expectations are assertions for data. They are the workhorse abstraction in Great Expectations, covering all kinds of common data issues. Expectations... -
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cuDF
GPU DataFrame Library
... with conda (miniconda, or the full Anaconda distribution) from the rapidsai channel. cuDF is supported only on Linux, and with Python versions 3.7 and later. The RAPIDS suite of open-source software libraries aims to enable the execution of end-to-end data science and analytics pipelines entirely on GPUs. It relies on NVIDIA® CUDA® primitives for low-level compute optimization but exposing that GPU parallelism and high-bandwidth memory speed through user-friendly Python interfaces. -
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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... -
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Orchest
Build data pipelines, the easy way
Code, run and monitor your data pipelines all from your browser! From idea to scheduled pipeline in hours, not days. Interactively build your data science pipelines in our visual pipeline editor. Versioned as a JSON file. Run scripts or Jupyter notebooks as steps in a pipeline. Python, R, Julia, JavaScript, and Bash are supported. Parameterize your pipelines and run them periodically on a cron schedule. Easily install language or system packages. Built on top of regular Docker container images...