Search Results for "track anomaly detection"
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Showing 41 open source projects for "track anomaly detection"
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Anomaly Detection Learning Resources
Anomaly detection related books, papers, videos, and toolboxes
Anomaly Detection Learning Resources is a curated open-source repository that collects educational materials, tools, and academic references related to anomaly detection and outlier analysis in data science. The project serves as a centralized index for researchers and practitioners who want to explore algorithms, datasets, and publications associated with detecting unusual patterns in data. -
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Anomalib
An anomaly detection library comprising state-of-the-art algorithms
Anomalib is an open-source deep learning library focused on anomaly detection and localization tasks, collecting state-of-the-art algorithms and tools under one modular framework. It provides implementations of leading anomaly detection methods drawn from current research, as well as a full set of utilities for training, evaluating, benchmarking, and deploying these models on both public and private datasets. -
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Python Outlier Detection
A Python toolbox for scalable outlier detection
PyOD is a comprehensive and scalable Python toolkit for detecting outlying objects in multivariate data. This exciting yet challenging field is commonly referred as outlier detection or anomaly detection. PyOD includes more than 30 detection algorithms, from classical LOF (SIGMOD 2000) to the latest COPOD (ICDM 2020) and SUOD (MLSys 2021). Since 2017, PyOD [AZNL19] has been successfully used in numerous academic researches and commercial products [AZHC+21, AZNHL19]. PyOD has multiple neural network-based models, e.g., AutoEncoders, which are implemented in both PyTorch and Tensorflow. ... -
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Orion
A machine learning library for detecting anomalies in signals
Orion is a machine-learning library built for unsupervised time series anomaly detection. Such signals are generated by a wide variety of systems, few examples include telemetry data generated by satellites, signals from wind turbines, and even stock market price tickers. We built this to provide one place where users can find the latest and greatest in machine learning and deep learning world including our own innovations. -
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FLEXible
Federated Learning (FL) experiment simulation in Python
FLEXible (Federated Learning Experiments) is a Python framework offering tools to simulate FL with deep learning. It includes built-in datasets (MNIST, CIFAR10, Shakespeare), supports TensorFlow/PyTorch, and has extensions for adversarial attacks, anomaly detection, and decision trees. -
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Elementary
Open-source data observability for analytics engineers
...Gain immediate visibility, detect data issues, send actionable alerts, and understand the impact and root cause. Generate a data observability report, host it or share with your team. Monitoring of data quality metrics, freshness, volume and schema changes, including anomaly detection. Elementary data monitors are configured and executed like native tests in dbt your project. Uploading and modeling of dbt artifacts, run and test results to tables as part of your runs. Get informative notifications on data issues, schema changes, models and tests failures. Inspect upstream and downstream dependencies to understand impact and root cause of data issues. -
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River ML
Online machine learning in Python
River is a Python library for online machine learning. It aims to be the most user-friendly library for doing machine learning on streaming data. River is the result of a merger between creme and scikit-multiflow. -
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Potpie
Create custom engineering agents for your codebase
Potpie is an AI-powered data analysis tool that automates the exploration and visualization of datasets, assisting users in uncovering insights without extensive coding. -
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Nixtla TimeGPT
TimeGPT-1: production ready pre-trained Time Series Foundation Model
TimeGPT is a production ready, generative pretrained transformer for time series. It's capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few lines of code. Whether you're a bank forecasting market trends or a startup predicting product demand, TimeGPT democratizes access to cutting-edge predictive insights, eliminating the need for a dedicated team of machine learning engineers. A generative model for time series. TimeGPT is capable of... -
Enterprise-grade ITSM, for every businessFreshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
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ContextGem
ContextGem: Effortless LLM extraction from documents
...It provides a flexible, intuitive API that minimizes boilerplate code, enabling developers to build complex extraction workflows efficiently. ContextGem supports various document formats and integrates with multiple LLM providers, making it a versatile tool for tasks like contract analysis, anomaly detection, and information retrieval. -
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Kronos
A Foundation Model for the Language of Financial Markets
...The system introduces a novel tokenization approach that converts continuous financial data into discrete tokens, enabling the model to process market behavior similarly to language. This allows Kronos to perform a variety of quantitative tasks such as forecasting, pattern recognition, and anomaly detection within financial datasets. It is optimized for the noisy and complex nature of market data, distinguishing it from general-purpose time-series models. The project includes multiple pre-trained model sizes and tools for fine-tuning, making it adaptable to different computational constraints and use cases. -
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leak-check
Personal Information “Leakage ” Detection Interface
leak-check is a utility designed to help developers detect memory leaks and resource mismanagement in applications. It provides tools to monitor allocations, track usage patterns, and identify potential leaks during runtime. The project focuses on improving application stability by highlighting inefficiencies in memory handling. It can be integrated into development workflows to catch issues early in the debugging process. leak-check is particularly useful in performance-critical... -
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changedetection.io
The best free open source website change detection and restock service
...Monitor out-of-stock products and get alerts when those products are back in stock, get restock alerts via Discord, Slack, email, and many other platforms. Using the browser steps configuration, add basic steps before performing change detection, such as logging into websites, adding a product to a cart, accepting cookie logins, entering dates, and refining searches. Monitor and track PDF file changes, and know when a PDF file has text changes. Know when your favourite product is on sale, or other special deals are announced before anyone else. Detect and monitor changes in JSON API responses. -
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OptScale
FinOps and MLOps platform to run ML/AI and regular cloud workloads
...Certified FinOps solution with the best cloud cost optimization engine, providing rightsizing recommendations, Reserved Instances/Savings Plans, and dozens of other optimization scenarios. With OptScale, users get complete cloud resource usage transparency, anomaly detection, and extensive functionality to avoid budget overruns. -
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TimeMixer
Decomposable Multiscale Mixing for Time Series Forecasting
TimeMixer is a deep learning framework designed for advanced time series forecasting and analysis using a multiscale neural architecture. The model focuses on decomposing time series data into multiple temporal scales in order to capture both short-term seasonal patterns and long-term trends. Instead of relying on traditional recurrent or transformer-based architectures, TimeMixer is implemented as a fully multilayer perceptron–based model that performs temporal mixing across different... -
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PyCaret
An open-source, low-code machine learning library in Python
PyCaret is an open-source, low-code machine learning library in Python that automates machine learning workflows. It is an end-to-end machine learning and model management tool that speeds up the experiment cycle exponentially and makes you more productive. In comparison with the other open-source machine learning libraries, PyCaret is an alternate low-code library that can be used to replace hundreds of lines of code with few lines only. This makes experiments exponentially fast and... -
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StatsForecast
Fast forecasting with statistical and econometric models
StatsForecast is a Python library for time-series forecasting that delivers a suite of classical statistical and econometric forecasting models optimized for high performance and scalability. It is designed not just for academic experiments but for production-level time-series forecasting, meaning it handles forecasting for many series at once, efficiently, reliably, and with minimal overhead. The library implements a broad set of models, including AutoARIMA, ETS, CES, Theta, plus a battery... -
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Granite TSFM
Foundation Models for Time Series
granite-tsfm collects public notebooks, utilities, and serving components for IBM’s Time Series Foundation Models (TSFM), giving practitioners a practical path from data prep to inference for forecasting and anomaly-detection use cases. The repository focuses on end-to-end workflows: loading data, building datasets, fine-tuning forecasters, running evaluations, and serving models. It documents the currently supported Python versions and points users to where the core TSFM models are hosted and how to wire up service components. Issues and examples in the tracker illustrate common tasks such as slicing inference windows or using pipeline helpers that return pandas DataFrames, grounding the library in day-to-day time-series operations. ... -
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OpenSpace
OpenSpace: Make Your Agents: Smarter, Low-Cost, Self-Evolving
OpenSpace is a self-evolving agent framework designed to improve the performance, efficiency, and collaboration of AI agents through continuous learning and shared knowledge. It introduces a system where agents develop reusable “skills” based on real task execution, allowing them to improve over time without retraining underlying models. The platform emphasizes collective intelligence, enabling multiple agents to share learned behaviors and benefit from each other’s experiences. It also... -
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LiveRecorder
A fully automatic live broadcast recording tool
LiveRecorder is an automated live stream recording tool designed to monitor and capture broadcasts from multiple streaming platforms without manual intervention. It continuously checks specified channels and begins recording automatically when a stream goes live, enabling hands-free archiving of content. The system supports a wide range of platforms including popular global and regional streaming services, making it versatile for different use cases. It relies on tools like Streamlink and... -
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pytype
A static type analyzer for Python code
pytype is a static type analyzer that checks and infers types for Python code without executing it, catching errors at “compile time” and generating actionable diagnostics. It grew alongside Python typing at Google and can understand both inline annotations and unannotated code via powerful inference. The tool consumes stub files (.pyi) for the standard library and third-party packages (from typeshed and its own built-ins), enabling accurate checks even in large, mixed-quality codebases.... -
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SSRFmap
Automatic SSRF fuzzer and exploitation tool
SSRFmap is a specialized security tool designed to automate the detection and exploitation of Server Side Request Forgery (SSRF) vulnerabilities. It takes as input a Burp request file and a user-specified parameter to fuzz, enabling you to fast-track the identification of SSRF attack surfaces. It includes multiple exploitation “modules” for common SSRF-based attacks or pivoting techniques, such as DNS zone transfers, MySQL/Postgres command execution, Docker API info leaks, and network scans. ... -
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OpenFieldAI - AI Open Field Test Tracker
OpenFieldAI is an AI based Open Field Test Rodent Tracker
OpenFieldAI use AI-CNN to track rodents movement with pretrained OFAI models , or user could create their own model with YOLOv8 for inferencing. The software generates Centroid graph, Heat map and Line path and a spreadsheet containing all calculated parameters like - Speed - Time in and out of ROI - Distance - Entries/Exits for single/multiple pre-recorded videos or live webcam video. The ROI is assigned automatically in multiple video input , and can be manually given in single... -
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SecurePose
Automated Face Blurring, Kinematics Extraction and Leg dystonia Dx
...The software provides clinical-grade face blurring with minimal manual effort. It was validated on videos recorded in clinical settings. The tool employs pose estimation to track and uniquely identify individuals, recognize patients, perform effective face blurring, and identify leg dystonia. SecurePose surpassed six existing methods in automated face detection and blurring and outperformed human performance in leg dystonia identification. This validation establishes its effectiveness and usability in clinically recorded gait videos for face blurring and kinematics extraction. ... -
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NuPIC
Numenta platform for intelligent computing
...At the core of HTM are time-based continuous learning algorithms that store and recall spatial and temporal patterns. NuPIC is suited to a variety of problems, particularly anomaly detection and prediction of streaming data sources. For more information, see numenta.org or the NuPIC Forum. If you want to build the dependent nupic.bindings from source, you should build and install from nupic.core prior to installing nupic (since a PyPI release will be installed if nupic.bindings isn't yet installed). To install from local source code, run from the repository root. ...
