Search Results for "statistical" - Page 2
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Showing 130 open source projects for "statistical"
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Wiz: #1 Cloud Security Software for Modern Cloud ProtectionUse the Wiz Cloud Security Platform to build faster in the cloud, enabling security, dev and devops to work together in a self-service model built for the scale and speed of your cloud development.
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Globalscape Enhanced File Transfer (EFT) is a best-in-class managed file transfer (MFT) solutionGlobalscape’s Enhanced File Transfer (EFT) platform is a comprehensive, user-friendly managed file transfer (MFT) software. Thousands of Windows-Centric Organizations trust Globalscape EFT for their mission-critical file transfers.
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Gretel Synthetics
Synthetic data generators for structured and unstructured text
...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. Need to synthesize one or multiple data types? We have you covered. Even take advantage or multimodal data generation. Synthesize and transform multiple tables or entire relational databases. ... -
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NeuralForecast
Scalable and user friendly neural forecasting algorithms.
...Unfortunately, available implementations and published research are yet to realize neural networks' potential. They are hard to use and continuously fail to improve over statistical methods while being computationally prohibitive. For this reason, we created NeuralForecast, a library favoring proven accurate and efficient models focusing on their usability. -
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Quantitative Trading System
A comprehensive quantitative trading system with AI-powered analysis
...The project is designed to provide an end-to-end infrastructure for building and operating algorithmic trading strategies in financial markets. It includes tools for collecting and processing market data from multiple sources, performing statistical and machine learning analysis, and generating trading signals based on quantitative models. The system supports real-time data streaming, allowing strategies to respond to market conditions as they evolve. QuantMuse also incorporates advanced risk management features, including portfolio monitoring, risk limits, and dynamic position sizing to control exposure. -
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NBA Sports Betting Machine Learning
NBA sports betting using machine learning
...Machine learning models are then trained to estimate the probability that a team will win a game as well as whether the total score will fall above or below the sportsbook’s predicted total. In addition to predicting outcomes, the project evaluates expected value to determine whether a potential bet offers a statistical advantage compared with sportsbook odds. -
MicroStation by Bentley Systems is the trusted computer-aided design (CAD) software built specifically for infrastructure design.MicroStation is the only computer-aided design software for infrastructure design, helping architects and engineers like you bring their vision to life, present their designs to their clients, and deliver their projects to the community.
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Lingua-Py
The most accurate natural language detection library for Python
Its task is simple: It tells you which language some text is written in. This is very useful as a preprocessing step for linguistic data in natural language processing applications such as text classification and spell checking. Other use cases, for instance, might include routing e-mails to the right geographically located customer service department, based on the e-mails' languages. Language detection is often done as part of large machine learning frameworks or natural language processing... -
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CodeChecker
CodeChecker is an analyzer tooling, defect database
CodeChecker is a static analysis infrastructure built on the LLVM/Clang Static Analyzer toolchain, replacing scan-build in a Linux or macOS (OS X) development environment. Executes Clang-Tidy and Clang Static Analyzer with Cross-Translation Unit analysis, Statistical Analysis (when checkers are available). Creates the JSON compilation database by wiretapping any build process (e.g., CodeChecker log -b "make"). Automatically analyzes GCC cross-compiled projects: detecting GCC or Clang compiler configuration and forming the corresponding clang analyzer invocations. Incremental analysis: Only the changed files and its dependencies need to be reanalyzed. ... -
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PyMC3
Probabilistic programming in Python
...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 in a model is not a scalar value or a fixed-length vector, but a function. A Gaussian process (GP) can be used as a prior probability distribution whose support is over the space of continuous functions. PyMC3 provides rich support for defining and using GPs. ... -
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BettaFish
Public opinion analysis system
...It uses a modular architecture of specialized agents that collaborate to crawl mainstream platforms, extract multimodal content like text and short video, and synthesize insights through both statistical and large language model techniques. With a design that lets users pose questions in natural language and receive structured reports, charts, and visualizations, the system aims to break information cocoons and provide comprehensive views of trends and public sentiment. Unlike simpler analytics tools, BettaFish employs agent collaboration and a “forum” style internal mechanism to combine diverse model outputs, making the analysis richer and more robust. ... -
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AI Marketing Skills
Open-source AI marketing skills for Claude Code
AI Marketing Skills is a comprehensive open-source framework designed to transform AI agents into fully operational marketing and sales systems by equipping them with structured, reusable “skills” that automate real business workflows. Instead of simple prompts, the project provides complete operational modules that include scripts, scoring systems, and decision-making logic, allowing AI tools like Claude Code to execute complex marketing tasks end-to-end. The system is organized into... -
Shoplogix Smart Factory PlatformReal-time Visibility into Your Shop Floor's Performance. The Shoplogix smart factory platform enables manufacturers to increase overall equipment effectiveness, reduce operational costs, sustain growth and improve profitability by allowing them to visualize, integrate and act on production and machine performance in real-time. Manufacturers that trust us to drive efficiency in their factories. Real-time visual data and analytics provide valuable insights to make better informed decisions. Uncover hidden shop floor potential and drive rapid time to value. Develop a continuously improving culture through training, education and data-driven decisions. Compete in the i4.0 world by making the Shoplogix Smart Factory Platform the cornerstone of your digital transformation. Connect to any equipment or device to automate data collection and exchange it with other manufacturing technologies. Automatically monitor, report and analyze machine states to track real-time production.
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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. ... -
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mlforecast
Scalable machine learning for time series forecasting
mlforecast is a time-series forecasting framework built around machine-learning models, designed to make forecasting both efficient and scalable. It lets you apply any regressor that follows the typical scikit-learn API, for example, gradient-boosted trees or linear models, to time-series data by automating much of the messy feature engineering and data preparation. Instead of writing custom code to build lagged features, rolling statistics, and date-based predictors, mlforecast generates... -
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AutoViz
Automatically Visualize any dataset, any size
...The system also includes built-in tools for evaluating data quality and identifying potential issues such as missing values or unusual distributions. By automating the visualization process, AutoViz allows users to rapidly explore datasets before applying machine learning models or statistical analysis. -
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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 consists a set of different GANs architectures developed using Tensorflow 2.0. ... -
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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... -
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seaborn
Statistical data visualization in Python
Seaborn is a Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics. Seaborn helps you explore and understand your data. Its plotting functions operate on dataframes and arrays containing whole datasets and internally perform the necessary semantic mapping and statistical aggregation to produce informative plots. Its dataset-oriented, declarative API lets you focus on what the different elements of your plots mean, rather than on the details of how to draw them. ... -
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Gwyddion
Scanning probe microscopy data visualisation and analysis
A data visualization and processing tool for scanning probe microscopy (SPM, i.e. AFM, STM, MFM, SNOM/NSOM, ...) and profilometry data, useful also for general image and 2D data analysis. -
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HEALPix
Data Analysis, Simulations and Visualization on the Sphere
Software for pixelization, hierarchical indexation, synthesis, analysis, and visualization of data on the sphere. Please acknowledge HEALPix by quoting the web page http://healpix.sourceforge.net (or https://healpix.sourceforge.io) and publication: K.M. Gorski et al., 2005, Ap.J., 622, p.759 Full software documentation available at https://healpix.sourceforge.io/documentation.php Wiki Pages: https://sourceforge.net/p/healpix/wiki/Home Exchanging Data with HEALPix (in FITS files):... -
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sadsa
SADSA (Software Application for Data Science and Analytics)
SADSA (Software Application for Data Science and Analytics) is a Python-based desktop application designed to simplify statistical analysis, machine learning, and data visualization for students, researchers, and data professionals. Built using Python for the GUI, SADSA provides a menu-driven interface for handling datasets, applying transformations, running advanced statistical tests, machine learning algorithms, and generating insightful plots — all without writing code. -
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Kalshi-Quant-TeleBot
Kalshi Advanced Quantitative Trading Bot is an enterprise-grade
...Built with a modular architecture, the system combines Python-based trading algorithms with a JavaScript Telegram bot interface for dynamic monitoring and interaction. The bot is designed to operate continuously, making data-driven decisions based on news sentiment analysis, statistical arbitrage opportunities -
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WhisperJAV
A subtitle generator for Japanese Adult Videos.
...Transformer-based ASR architectures like Whisper suffer significant performance degradation when applied to the spontaneous and noisy domain of JAV. This degradation is driven by specific acoustic and temporal characteristics that defy the statistical distributions of standard training data. -
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SPPAS
SPPAS - the automatic annotation and analyses of speech
...SPPAS is able to produce automatically speech annotations from a recorded speech sound and its orthographic transcription. SPPAS is helpful for the analysis of any annotated data: estimate statistical distributions, make requests, manage files, visualize annotations. SPPAS offers a file converter from/to a wide range of formats: xra, TextGrid, eaf, trs... <https://sppas.org> -
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Chemical Trajectory Analyzer
A software package for processing and analyzing chemical trajectories
...-D.Przybylski-Freund, L.C.Kröger, W.A.Kopp, A.E.Ismail, K.Leonhard, "Automated Discovery of Reaction Pathways, Rate Constants, and Transition States Using Reactive Molecular Dynamics Simulations", J. Chem. Theory Comput. 11 (2015), 2517-2524 L.C.Kröger, W.A.Kopp, M.Döntgen, K.Leonhard, "Assessing Statistical Uncertainties of Rare Events in Reactive Molecular Dynamics Simulations", J. Chem. Theory Comput. 13 (2017), 3955-3960 M.Döntgen, F.Schmalz, W.A.Kopp, L.C.Kröger, K.Leonhard, "Automated Chemical Kinetic Modeling via Hybrid Reactive Molecular Dynamics and Quantum Chemistry Simulations", J. Chem. Inf. Model. 58 (2018), 1343-1355 Check the Wiki for bug reports and fixes. -
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The Sashimi project hosts the Trans-Proteomic Pipeline (TPP), a mature suite of tools for mass-spec (MS, MS/MS) based proteomics: statistical validation, quantitation, visualization, and converters from raw MS data to the open mzML/mzXML formats.
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Dodge gpt
Bypass Ai content for GPTZero and others making text Undetectable
*New Update* ╔════════════════════════════════════════════════════════════════╗ ║ DODGE V10 - STEALTH EDITION ║ The Only AI Text Humanizer That Defeats GPTZero ╚════════════════════════════════════════════════════════════════╝ █████████████████████████████████████████████████████████████████ █ █ █ 🛡️ CURRENT STATUS: GPTZERO RESISTANT - VERIFIED 2026 █ █ 📊 SUCCESS RATE: 60.7% AGAINST ALL DETECTORS █ █ 🔬 BASED ON: REAL HUMAN CORPUS ANALYSIS █ █ █ █████████████████████████████████████████████████████████████████ Dodge V10 isn't just another "synonym replacer" or "typo adder". It is a sophisticated neural text transformation engine that rewrites content to match the EXACT statistical fingerprint of human writing. -----100% Free----- -
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Meshwork Analysis terminal
Quantitative analytical Finance Terminal
MWA Finance Terminal allows users to research and obtain data about various financial instruments and allows them to perform Statistical analysis with Various ML Technologies. It's divided into Modules and Options within them.
