Search Results for "data capture framework"
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Showing 17 open source projects for "data capture framework"
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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.
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Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
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FATE
An industrial grade federated learning framework
FATE (Federated AI Technology Enabler) is the world's first industrial grade federated learning open source framework to enable enterprises and institutions to collaborate on data while protecting data security and privacy. It implements secure computation protocols based on homomorphic encryption and multi-party computation (MPC). Supporting various federated learning scenarios, FATE now provides a host of federated learning algorithms, including logistic regression, tree-based algorithms, deep learning and transfer learning. ... -
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Python Outlier Detection
A Python toolbox for scalable outlier detection
...PyOD contains multiple models that also exist in scikit-learn. It is possible to train and predict with a large number of detection models in PyOD by leveraging SUOD framework. A benchmark is supplied for select algorithms to provide an overview of the implemented models. In total, 17 benchmark datasets are used for comparison, which can be downloaded at ODDS. -
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MOA - Massive Online Analysis
Big Data Stream Analytics Framework.
A framework for learning from a continuous supply of examples, a data stream. Includes classification, regression, clustering, outlier detection and recommender systems. Related to the WEKA project, also written in Java, while scaling to adaptive large scale machine learning. -
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Active Learning
Framework and examples for active learning with machine learning model
Active Learning is a Python-based research framework developed by Google for experimenting with and benchmarking various active learning algorithms. It provides modular tools for running reproducible experiments across different datasets, sampling strategies, and machine learning models. The system allows researchers to study how models can improve labeling efficiency by selectively querying the most informative data points rather than relying on uniformly sampled training sets. ... -
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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Code Catalog in Python
Algorithms and data structures for review for coding interview
code-catalog-python serves as a grab-bag of small, readable Python examples that illustrate common algorithms, data structures, and utility patterns. Each snippet aims to be self-contained and easy to study, with clear inputs, outputs, and the essential logic on display. The catalog format lets you scan for an example, copy it, and adapt it to your use case without wading through a large framework. It favors clarity over micro-optimizations so learners can grasp the idea before worrying about edge performance. ... -
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CognitionMaster
object-based image analysis framework
Wienert S, Heim D, Kotani M, Lindequist B, Stenzinger A, Ishii M, Hufnagl P, Beil M, Dietel M, Denkert C, Klauschen F. CognitionMaster: an object-based image analysis framework. Diagn Pathol 2013, 8:34 -
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CoRoPa stands for Computational Rough Paths. The aim of CoRoPa is to provide a software framework for various ideas related to Rough Path Theory, including rough differential equations and the digital description of serial data streams.
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The Modular toolkit for Data Processing (MDP) is a Python data processing framework. From the user's perspective, MDP is a collection of supervised and unsupervised learning algorithms and other data processing units that can be combined into data processing sequences and more complex feed-forward network architectures. From the scientific developer's perspective, MDP is a modular framework, which can easily be expanded.
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S-Match
S-Match is a semantic matching framework.
S-Match is a semantic matching framework. S-Match takes any two tree like structures (such as database schemas, classifications, lightweight ontologies) and returns a set of correspondences between those tree nodes which semantically correspond to one another. S-Match contains implementations of the semantic matching, minimal semantic matching and structure preserving semantic matching algorithms. S-Match applies as a solution in many fields, including: information integration,... -
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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CADI is an implementation of the JPIP standard (JPEG2000 Interactive Protocol - Part 9). CADI includes a JPIP server, a JPIP proxy, and a JPIP Client. CADI is designed and programmed with the aim to provide a flexible framework to test and develop ne
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HDRFlow is a framework to process high-dynamic range (HDR) and RAW images. It's written in C++, and is both cross-platform and hardware accelerated on modern GPUs.
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Public description: The 'cbear' framework is a set of libraries and common utilities for different programming languages and platforms.
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Very useful framework library, contains many frequent used code snippets, algorithms, data structures, WinForms & APS.NET controls for all-day work.
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This is an image coder with fixed sampling, at a rate of up to 24 images per second (on XC2V1000-4 @ 40 MHz with res. up to 352x288).
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Bookinex is an application designed to index your collection of books, it supports scanning of Barcodes to recognize ISB Numbers and querying web services to collect data.
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GraphSmart is a collection of graph data structures and algorithms utilizing generics and the Microsoft .NET 2.0 Framework. Included items are commonly used in software engineering but not included in the .NET 2.0 Framework class library.
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EpFamvir
C++ Software framework that supports data-intensive distributed apps.
* EpFamvirproject in this site is not maintained anymore. * The project has been moved to https://github.com/juhgiyo/EpFamvir EpFamvir is a Visual C++ Software framework that supports data-intensive distributed applications.. The features includes: - Famvir Distributed File System - Job Tracker and Task Tracker: the MapReduce Engine For detailed documentation, please download this full document (EPFamvir Documentation.chm) from the "Downloads" Section. * If the documentation file is not visible after finishing download. ...
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