Search Results for "statistics" - Page 7
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Showing 1885 open source projects for "statistics"
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Book6_First-Course-in-Data-Science
From Addition, Subtraction, Multiplication, and Division to ML
...The repository contains draft chapters, supporting Python code, and visual materials designed to guide readers from basic mathematical operations toward practical machine learning understanding. The goal of the project is to make complex topics such as statistics, algorithms, and data analysis more accessible to learners by breaking concepts into clear explanations supported by code examples and diagrams. The material emphasizes a learning approach that combines theoretical knowledge with hands-on experimentation, often recommending interactive tools such as Jupyter notebooks to explore the ideas presented in the book. -
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forecast
Forecasting Functions for Time Series and Linear Models
...It provides functions for building, assessing, and using univariate forecasting models (e.g. ARIMA, exponential smoothing, etc.), tools for automatic model selection, diagnostics, plotting, forecasting future values, etc. It's widely used in statistics, economics, business forecasting, environmental science, etc. Exponential smoothing state space models (ETS) including seasonal components. Residual checks, model accuracy, plots, forecast error measures etc. -
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Peroxide
Rust numeric library with high performance and friendly syntax
Rust numeric library contains linear algebra, numerical analysis, statistics and machine learning tools with R, MATLAB, Python-like macros. Peroxide uses a 1D data structure to represent matrices, making it straightforward to integrate with BLAS (Basic Linear Algebra Subprograms). This means that Peroxide can guarantee excellent performance for linear algebraic computations by leveraging the optimized routines provided by BLAS. -
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NeuroMatch Academy (NMA)
NMA Computational Neuroscience course
...You will learn how to code in Python from scratch using a simple neural model, the leaky integrate-and-fire model, as a motivation. Then, you will cover linear algebra, calculus and probability & statistics. The topics covered on these days were carefully chosen based on what you need for the comp neuro course. -
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ydata-profiling
Create HTML profiling reports from pandas DataFrame objects
ydata-profiling primary goal is to provide a one-line Exploratory Data Analysis (EDA) experience in a consistent and fast solution. Like pandas df.describe() function, that is so handy, ydata-profiling delivers an extended analysis of a DataFrame while allowing the data analysis to be exported in different formats such as html and json. -
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Maths, CS & AI Compendium
Become a cracked AI/ML Research Engineer
Maths, CS & AI Compendium is an open educational project that explains mathematics, computing, and artificial intelligence from foundational concepts through advanced engineering topics. It favors intuition, practical context, and connected explanations over dense textbook notation. Its chapters cover vectors, matrices, calculus, statistics, probability, machine learning, language processing, computer vision, speech, multimodal learning, robotics, and graph neural networks. It also addresses operating systems, algorithms, production software, GPU programming, AI inference, and ML systems design. Readers need only elementary mathematics and basic Python knowledge to begin. ... -
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OSRS .json Hiscores
The Oldschool Runescape API wrapper that does more
...It also adds additional logic to determine player game modes, including historical transitions such as de-ironing or hardcore status changes. The library includes functions for retrieving leaderboard pages, skill rankings, and activity statistics, making it suitable for building analytics dashboards or game-related applications. It supports TypeScript with full type definitions, improving developer experience and reliability when integrating into backend systems. -
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MyPerf4J
High performance Java APM. Powered by ASM
MyPerf4J is an open source Java performance monitoring and profiling tool designed to help developers and operations teams analyze application behavior with minimal overhead. It focuses on providing lightweight yet high-precision metrics collection for method execution times, throughput, and latency, making it particularly useful in high-performance production environments. The project emphasizes low performance impact by using efficient time recording and aggregation techniques, allowing... -
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Statsviz
Visualize Go runtime metrics in real time
...By registering HTTP handlers in an application, developers can instantly expose live charts showing heap usage, garbage collection activity, goroutines, scheduler behavior, and other runtime statistics. The system streams metrics to the browser via WebSocket, enabling near-real-time updates with minimal overhead. statsviz is designed to integrate easily into existing Go services and supports customization such as alternate routes, middleware integration, and user-defined plots. Its visual interface includes filtering controls, time-range selection, and the ability to pause updates for closer inspection. ... -
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Flower
Real-time monitor and web admin for Celery distributed task queue
Flower is an open-source web application that provides real-time monitoring and administrative control for Celery distributed task queues. It exposes detailed visibility into worker status, task execution history, and queue metrics through an interactive web dashboard. Developers and operators can remotely manage workers by restarting instances, adjusting pool sizes, revoking tasks, or applying rate limits without direct server access. Flower also supports broker monitoring and integrates... -
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Amper
Build tool for the Kotlin and Java languages
Amper is an open-source data collection and metric reporting agent developed by JetBrains as part of their internal analytics and telemetry infrastructure for IntelliJ-based products. Its purpose is to gather usage statistics, performance metrics, error reports, and other diagnostic signals from IDE installations in a privacy-conscious way to help product teams understand real-world usage patterns and improve quality. Designed to be lightweight and efficient, Amper runs as a background service that batches and securely transmits anonymous data back to analytics pipelines while respecting user privacy settings and opt-outs. ... -
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GrowthBook
Open source feature flagging and AB testing platform
...The platform is designed for performance and scale: its SDKs are lightweight, supporting local evaluation to minimize latency, and it integrates deeply with existing data stacks so you can use your warehouse or analytics system as the source of truth. Experimentation in GrowthBook isn’t just toggles; its statistics engine supports advanced techniques like CUPED, Bayesian, and sequential testing, and control group checks so you can confidently measure impact. -
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EPLB
Expert Parallelism Load Balancer
EPLB is DeepSeek’s open implementation of a load balancing algorithm designed for expert parallelism (EP) settings in MoE architectures. In EP, different “experts” are mapped to different GPUs or nodes, so load imbalance becomes a performance bottleneck if certain experts are invoked much more often. EPLB solves this by duplicating heavily used experts (redundancy) and then placing those duplicates across GPUs to even out computational load. It uses policies like hierarchical load balancing... -
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clusterProfiler
A universal enrichment tool for interpreting omics data
clusterProfiler is an R/Bioconductor package that provides a unified workflow for functional enrichment analysis to interpret high-throughput omics results. It supports both over-representation analysis and gene set enrichment analysis, letting you work with unranked gene lists or ranked statistics from differential pipelines. The package connects to multiple knowledge bases—such as Gene Ontology, KEGG, Reactome, Disease Ontology, MeSH and others—through a consistent interface so you can query different biological lenses without rewriting code. It is designed for breadth, covering coding and non-coding features and thousands of organisms by leveraging continuously updated annotations. ... -
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targets
Function-oriented Make-like declarative workflows for R
The targets package is a pipeline / workflow management tool in R, designed to coordinate multi‐step computational workflows in data science / statistics. It tracks dependencies between “targets” (computational steps), skips steps whose upstream data or code hasn’t changed, supports parallel computation, branching (dynamic generation of sub‐targets), file format abstractions, and encourages reproducible and efficient analyses. It’s something like GNU Make for R, but more integrated. ... -
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endlessh-go
A golang implementation of endlessh exporting Prometheus metrics
Endlessh is a great idea that not only blocks the brute force SSH attacks, but also wastes attackers time as a kind of counter-attack. Besides trapping the attackers, I also want to visualize the Geolocations and other statistics of the sources of attacks. Unfortunately the wonderful original C implementation of endlessh only provides text based log, but I do not like the solution that writes extra scripts to parse the log outputs, then exports the results to a dashboard, because it would introduce extra layers in my current setup and it would depend on the format of the text log file rather than some structured data. ... -
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loonflow
A workflow engine base on django python
a workflow engine base on django The django-based workflow engine system (called through the http interface, can be used as a unified workflow engine within the enterprise, providing all workflows such as permission application, resource application, release application, leave, reimbursement, it service, etc. Scenario services), if there is a certain development capability, it is recommended to use only the back-end engine function, and the front-end customized development according to the... -
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GPU Hot
Real-time NVIDIA GPU dashboard
GPU Hot is an open-source, lightweight monitoring dashboard designed to provide real-time visibility into NVIDIA GPU performance across single machines or entire clusters. The project offers a self-hosted web interface that streams hardware metrics directly from GPU servers, enabling developers, ML engineers, and system administrators to observe GPU utilization and system behavior in real time through a browser. The dashboard collects and displays a wide range of performance metrics... -
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Java Tablesaw
Java dataframe and visualization library
Tablesaw is a dataframe and visualization library that supports loading, cleaning, transforming, filtering, and summarizing data. If you work with data in Java, it may save you time and effort. Tablesaw also supports descriptive statistics and can be used to prepare data for working with machine learning libraries like Smile, Tribuo, H20.ai, DL4J. Import data from RDBMS, Excel, CSV, TSV, JSON, HTML, or Fixed Width text files, whether they are local or remote (http, S3, etc.) Tablesaw supports data visualization by providing a wrapper for the Plot.ly JavaScript plotting library. ... -
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Riemann
A network event stream processing system, in Clojure
Riemann aggregates events from your servers and applications with a powerful stream processing language. Send an email for every exception in your app. Track the latency distribution of your web app. See the top processes on any host, by memory and CPU. Combine statistics from every Riak node in your cluster and forward to Graphite. Track user activity from second to second. Riemann streams are just functions which accept an event. Events are just structs with some common fields like :host and :service You can use dozens of built-in streams for filtering, altering, and combining events, or write your own. ... -
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ReDex
A bytecode optimizer for Android apps
ReDex is an Android bytecode (dex) optimizer originally developed at Facebook. It provides a framework for reading, writing, and analyzing .dex files, and a set of optimization passes that use this framework to improve the bytecode. An APK optimized by ReDex should be smaller and faster than its source. Redex provides a framework for reading, writing, and analyzing .dex files, and a set of optimization passes that use this framework to improve the bytecode. An APK optimized by Redex should... -
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Bull
Queue package for handling distributed jobs and messages in NodeJS
...Supercharge your queues with a professional front end. Get a complete overview of all your queues. Inspect jobs, search, retry, or promote delayed jobs. Metrics and statistics, and many more features. Queues are robust and can be run in parallel in several threads or processes without any risk of hazards or queue corruption. -
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SDGym
Benchmarking synthetic data generation methods
The Synthetic Data Gym (SDGym) is a benchmarking framework for modeling and generating synthetic data. Measure performance and memory usage across different synthetic data modeling techniques – classical statistics, deep learning and more! The SDGym library integrates with the Synthetic Data Vault ecosystem. You can use any of its synthesizers, datasets or metrics for benchmarking. You also customize the process to include your own work. Select any of the publicly available datasets from the SDV project, or input your own data. Choose from any of the SDV synthesizers and baselines. ... -
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libvips
A fast image processing library with low memory needs
...Compared to similar libraries, libvips runs quickly and uses little memory. libvips is licensed under the LGPL 2.1+. It has around 300 operations covering arithmetic, histograms, convolution, morphological operations, frequency filtering, colour, resampling, statistics and others. It supports a large range of numeric types, from 8-bit int to 128-bit complex. Images can have any number of bands. It supports a good range of image formats, including JPEG, JPEG2000, JPEG-XL, TIFF, PNG, WebP, HEIC, AVIF, FITS, Matlab, OpenEXR, PDF, SVG, HDR, PPM / PGM / PFM, CSV, GIF, Analyze, NIfTI, DeepZoom, and OpenSlide. ... -
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chatanalytics.app
Generate interactive, beautiful and insightful chat analysis reports
...It supports exports from platforms such as Discord, Messenger, Telegram, and WhatsApp, depending on the available export format. The app generates a single HTML report with statistics, graphs, timelines, emoji analysis, links, calls, interactions, language data, and sentiment information. Its main privacy advantage is that chat data stays in the browser while reports are generated. Users can also run it from the command line or self-host it with Docker. It is useful for people who want to explore conversation patterns without uploading private messages to a third-party analysis service.
