Search Results for "genstat statistical software"
Sort By:
Showing 28 open source projects for "genstat statistical software"
View related business solutions-
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.
-
Gemini 3 and 200+ AI Models on One PlatformBuild generative AI apps with Vertex AI. Switch between models without switching platforms.
-
1
statsmodels
Statsmodels, statistical modeling and econometrics in Python
statsmodels is a Python module that provides classes and functions for the estimation of many different statistical models, as well as for conducting statistical tests, and statistical data exploration. An extensive list of result statistics are available for each estimator. The results are tested against existing statistical packages to ensure that they are correct. The package is released under the open source Modified BSD (3-clause) license. Generalized linear models with support for all... -
2
spaCy
Industrial-strength Natural Language Processing (NLP)
spaCy is a library built on the very latest research for advanced Natural Language Processing (NLP) in Python and Cython. Since its inception it was designed to be used for real world applications-- for building real products and gathering real insights. It comes with pretrained statistical models and word vectors, convolutional neural network models, easy deep learning integration and so much more. spaCy is the fastest syntactic parser in the world according to independent benchmarks, with... -
3
Edit Banana
Edit Banana: A framework for converting statistical figures
Edit Banana is an innovative web application designed to simplify image editing by merging intuitive user interfaces with powerful generative AI capabilities, enabling users to quickly enhance, manipulate, or transform photos without needing advanced design skills. It provides a smooth, browser-based experience where users can upload images, make precise edits such as background removal or inpainting, and apply stylistic transformations or corrections through AI prompts. The tool focuses on... -
4
WeasyPrint
The awesome document factory
WeasyPrint is a smart solution helping people to create PDF documents. You can generate gorgeous statistical reports, invoices, tickets, and anything you want as long as you have some webdesign skills! Design your documents just as you design your websites! WeasyPrint follows the widely used HTML and CSS specifications from the W3C. You can use your usual web tools, languages and frameworks, but for print. Creating high-quality digital documents requires features that you love to use as... -
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
-
5
plotly.py
The interactive graphing library for Python
plotly.py is a browser-based, open source graphing library for Python that lets you create beautiful, interactive, publication-quality graphs. Built on top of plotly.js, it is a high-level, declarative charting library that ships with more than 30 chart types. Everything from statistical charts and scientific charts, through to maps, 3D graphs and animations, plotly.py lets you create them all. Graphs made with plotly.py can be viewed in Jupyter notebooks, standalone HTML files, or hosted... -
6
PyMC3
Probabilistic programming in Python
PyMC3 allows you to write down models using an intuitive syntax to describe a data generating process. Fit your model using gradient-based MCMC algorithms like NUTS, using ADVI for fast approximate inference — including minibatch-ADVI for scaling to large datasets, or using Gaussian processes to build Bayesian nonparametric models. PyMC3 includes a comprehensive set of pre-defined statistical distributions that can be used as model building blocks. Sometimes an unknown parameter or variable... -
7
Copulas
A library to model multivariate data using copulas
Copulas is a Python library for modeling multivariate distributions and sampling from them using copula functions. Given a table of numerical data, use Copulas to learn the distribution and generate new synthetic data following the same statistical properties. Choose from a variety of univariate distributions and copulas – including Archimedian Copulas, Gaussian Copulas and Vine Copulas. Compare real and synthetic data visually after building your model. Visualizations are available as 1D... -
8
Gretel Synthetics
Synthetic data generators for structured and unstructured text
Unlock unlimited possibilities with synthetic data. Share, create, and augment data with cutting-edge generative AI. Generate unlimited data in minutes with synthetic data delivered as-a-service. Synthesize data that are as good or better than your original dataset, and maintain relationships and statistical insights. Customize privacy settings so that data is always safe while remaining useful for downstream workflows. Ensure data accuracy and privacy confidently with expert-grade reports.... -
9
Synthetic Data Vault (SDV)
Synthetic Data Generation for tabular, relational and time series data
The Synthetic Data Vault (SDV) is a Synthetic Data Generation ecosystem of libraries that allows users to easily learn single-table, multi-table and timeseries datasets to later on generate new Synthetic Data that has the same format and statistical properties as the original dataset. Synthetic data can then be used to supplement, augment and in some cases replace real data when training Machine Learning models. Additionally, it enables the testing of Machine Learning or other data dependent software systems without the risk of exposure that comes with data disclosure. Underneath the hood it uses several probabilistic graphical modeling and deep learning based techniques. ... -
Powerful App Monitoring Without Surprise BillsTired of monitoring tools that punish you for scaling? AppSignal offers transparent, predictable pricing with every feature unlocked on every plan. Track errors, monitor performance, detect anomalies, and manage logs across Ruby, Python, Node.js, and more. Trusted by developers since 2012 with free dev-to-dev support. No credit card required to start your 30-day trial.
-
10
Union Pandera
Light-weight, flexible, expressive statistical data testing library
The open-source framework for precision data testing for data scientists and ML engineers. Pandera provides a simple, flexible, and extensible data-testing framework for validating not only your data but also the functions that produce them. A simple, zero-configuration data testing framework for data scientists and ML engineers seeking correctness. Access a comprehensive suite of built-in tests, or easily create your own validation rules for your specific use cases. Validate the functions... -
11
YData Synthetic
Synthetic data generators for tabular and time-series data
A package to generate synthetic tabular and time-series data leveraging state-of-the-art generative models. Synthetic data is artificially generated data that is not collected from real-world events. It replicates the statistical components of real data without containing any identifiable information, ensuring individuals' privacy. This repository contains material related to Generative Adversarial Networks for synthetic data generation, in particular regular tabular data and time-series. It... -
12
Darts
A python library for easy manipulation and forecasting of time series
darts is a Python library for easy manipulation and forecasting of time series. It contains a variety of models, from classics such as ARIMA to deep neural networks. The models can all be used in the same way, using fit() and predict() functions, similar to scikit-learn. The library also makes it easy to backtest models, combine the predictions of several models, and take external data into account. Darts supports both univariate and multivariate time series and models. The ML-based models... -
13
FuzzBench
FuzzBench - Fuzzer benchmarking as a service
FuzzBench is a large-scale, open research platform developed by Google to evaluate and benchmark fuzzers — automated software testing tools that detect vulnerabilities through randomized input generation. It provides a standardized, reproducible environment for comparing the performance and effectiveness of different fuzzing algorithms on real-world software targets. FuzzBench integrates with the OSS-Fuzz infrastructure, allowing it to run experiments on authentic open source projects and collect meaningful data on crash discovery rates, code coverage, and bug-finding efficiency. ... -
14
whiteboxgui
An interactive GUI for WhiteboxTools in a Jupyter-based environment
The whiteboxgui Python package is a Jupyter frontend for WhiteboxTools, an advanced geospatial data analysis platform developed by Prof. John Lindsay (webpage; jblindsay) at the University of Guelph's Geomorphometry and Hydrogeomatics Research Group. WhiteboxTools can be used to perform common geographical information systems (GIS) analysis operations, such as cost-distance analysis, distance buffering, and raster reclassification. Remote sensing and image processing tasks include image... -
15
m2cgen
Transform ML models into a native code
m2cgen (Model 2 Code Generator) - is a lightweight library that provides an easy way to transpile trained statistical models into a native code (Python, C, Java, Go, JavaScript, Visual Basic, C#, PowerShell, R, PHP, Dart, Haskell, Ruby, F#, Rust, Elixir). Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies. Some models force input data to be particular type during prediction phase... -
16
Raiden Network
Raiden Network
Use Raiden to enrich your dApp with nearly instant, low-fee and scalable payments. It comes with an easy-to-use API and is compatible with the Ethereum ERC20 token standard. Incentivized, decentralized P2P live streaming with micropayments using Raiden, introducing “Proof-of-Stream-Payment”. The Raiden Network is an infrastructure layer on top of the Ethereum Blockchain. While the basic idea is simple, the underlying protocol is quite complex and the implementation non-trivial. Nonetheless... -
17
abu
Abu quantitative trading system (stocks, options, futures, bitcoin)
Abu Quantitative Integrated AI Big Data System, K-Line Pattern System, Classic Indicator System, Trend Analysis System, Time Series Dimension System, Statistical Probability System, and Traditional Moving Average System conduct in-depth quantitative analysis of investment varieties, completely crossing the user's complex code quantification stage, more suitable for ordinary people to use, towards the era of vectorization 2.0. The above system combines hundreds of seed quantitative models,... -
18
CTS Surveyor
Foot traffic and facial analytics for your business and home
Surveyor is a software solution that monitors its environment via camera and gathers demographic information about the public in the surrounding area, providing important statistics such as number of people passing by as well as providing facial analytics to classify the pedestrians based on their age and gender. The statistical data is stored in a local database and is made available via RESTful API’s, and easy integration with other applications can be accomplished via a WebSocket interface that provides live notifications about people in the camera’s field of view At the moment, the solutions is available for Windows only, with Linux version coming soon – please see our User Guide at http://caerustech-solutions.com/demo/User_Guide.pdf Sample Python client: https://github.com/CaerustechSolutions/cts-surveyor-pyclient Contact Us: http://caerustech-solutions.com/contact-us/ -
19
Waterloo
Java-based scientific graphics
Java-based scientific graphics with support for Java, Groovy, MATLAB, Python, the R statistical environment, Scala and SciLab. -
20
Gitinspector
The statistical analysis tool for git repositories
Gitinspector is a statistical analysis tool for git repositories. The default analysis shows general statistics per author, which can be complemented with a timeline analysis that shows the workload and activity of each author. Under normal operation, it filters the results to only show statistics about a number of given extensions and by default only includes source files in the statistical analysis. This tool was originally written to help fetch repository statistics from student projects... -
21
A python module that provides algorithms for advanced search - basically all you need to build a search engine.
-
22
Please participate in the SURVEY on rgedit's future: https://www.surveymonkey.com/s/VNMMJMJ your answers are much appreciated! Gedit (Gnome editor, www.gedit.org) plug-in allowing it to become an easy-to-use and yet light-weight IDE for the statistical programming environment, R (www.r-project.org).
-
23
GISBox by Citiviz
Ready-to-use appliance for GIS, Data Mining and Analysis, Modelling...
GISBox by Citiviz is a ready-to-use virtual appliance containing an assortment of powerful, free and open source GIS, Data Mining and Analysis, Modelling and Programming software and packages. The pre-configured and tested GISBox allows you to try and use in few minutes a variety of software used by data scientists, engineers, physicists, mathematicians, geomatics engineers, and geographers from around the globe, without installing anything more than once the Oracle VirtualBox™ software... -
24
The purpose of the Metabrain library is to give developers a way to extract this information from the Internet without resorting to natural language parsing or other complex techniques, using instead statistical methods and patterns/trends analysis.
-
25
PyAnnotation is a Python Library to access and manipulate linguistically annotated corpus files. Supported file formats are Kura XML, Elan XML and Toolbox files. A Corpus Reader API is provided to support statistical analysis within the NLTK.
