Search Results for "modular" - Page 3
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Showing 87 open source projects for "modular"
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MMF
A modular framework for vision & language multimodal research
...MMF is built on top of PyTorch that brings all of its power in your hands. MMF is not strongly opinionated. So you can use all of your PyTorch knowledge here. MMF is created to be easily extensible and composable. Through our modular design, you can use specific components from MMF that you care about. Our configuration system allows MMF to easily adapt to your needs. -
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TF Quant Finance
High-performance TensorFlow library for quantitative finance
...Users can value options and fixed-income instruments, simulate paths, fit curves, and calibrate models while leveraging TensorFlow’s jit compilation and automatic differentiation. The codebase is organized as modular math and finance primitives so you can combine building blocks or target end-to-end examples. It includes Bazel builds, tests, and example notebooks to accelerate learning and adoption in real workflows. With hardware acceleration and differentiable models, it enables modern techniques like gradient-based calibration and end-to-end learning of market dynamics. -
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WALKOFF
A flexible, easy to use, automation framework
Faster, smarter, cheaper operations through automation. WALKOFF puts the tools in your hands to easily automate the tedious repetitive tasks dragging your operations down. Act smarter with WALKOFF by automatically gathering data, analyzing data, or visualizing data customized to your requirements. Act faster with WALKOFF by integrating the capabilities you already own to dynamically respond on your terms to your fast-moving environment. Drag and drop workflow editor. Sharable apps and... -
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Coach
Enables easy experimentation with state of the art algorithms
Coach is a python framework that models the interaction between an agent and an environment in a modular way. With Coach, it is possible to model an agent by combining various building blocks, and training the agent on multiple environments. The available environments allow testing the agent in different fields such as robotics, autonomous driving, games and more. It exposes a set of easy-to-use APIs for experimenting with new RL algorithms and allows simple integration of new environments to solve. ... -
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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. The main experiment runner (run_experiment.py) supports a wide range of configurations, including batch sizes, dataset subsets, model selection, and data preprocessing options. ... -
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Invenio
Invenio digital library framework
...Developed by CERN, it is designed to manage, index, and provide access to metadata-rich content such as publications, datasets, and multimedia files. Invenio provides a modular architecture, making it suitable for libraries, archives, and research institutions. -
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Video Nonlocal Net
Non-local Neural Networks for Video Classification
video-nonlocal-net implements Non-local Neural Networks for video understanding, adding long-range dependency modeling to 2D/3D ConvNet backbones. Non-local blocks compute attention-like responses across all positions in space-time, allowing a feature at one frame and location to aggregate information from distant frames and regions. This formulation improves action recognition and spatiotemporal reasoning, especially for classes requiring context beyond short temporal windows. The repo... -
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Gin Config
Gin provides a lightweight configuration framework for Python
...By decorating functions and classes with @gin.configurable, Gin allows their parameters to be overridden using simple configuration files (.gin) or command-line bindings. Users can define default parameter values, scoped configurations, and modular references to functions, classes, or instances, resulting in highly composable and dynamic experiment setups. Gin is particularly popular in TensorFlow and PyTorch projects, where researchers and developers need to tune numerous interdependent parameters across models, datasets, optimizers, and training pipelines. -
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jsondata
Modular JSON by trees and branches, pointers and patches
The 'jsondata' package provides for the modular in-memory processing of JSON data by trees, branches, pointers, and patches. The main interface classes are: - JSONData - Core for RFC7159 based data structures. Provides modular data components. - JSONDataSerializer - Core for RFC7159 based data persistence. Provides modular data serialization. - JSONPointer - RFC6901 for addressing by pointer paths. -
Total Network Visibility for Network Engineers and IT ManagersThis means every device on your network, and every interface on every device is automatically analyzed for performance, errors, QoS, and configuration.
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Needle
The iOS Security Testing Framework
...The Android ecosystem has tools like "drozer" that have solved this problem and aim to be a ‘one-stop shop’ for the majority of use cases, however, iOS does not have an equivalent. Needle is the MWR's iOS Security Testing Framework, released at Black Hat USA in August 2016. It is an open-source modular framework. -
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TensorFlow World
Simple and ready-to-use tutorials for TensorFlow
...Deep Learning is in very high interest these days - there's a crucial need for rapid and optimized implementations of the algorithms and architectures. TensorFlow is designed to facilitate this goal. The strong advantage of TensorFlow is it flexibility in designing highly modular models which can also be a disadvantage for beginners since a lot of the pieces must be considered together when creating the model. -
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seq2seq
A general-purpose encoder-decoder framework for Tensorflow
seq2seq is an early, influential TensorFlow reference implementation for sequence-to-sequence learning with attention, covering tasks like neural machine translation, summarization, and dialogue. It packaged encoders, decoders, attention mechanisms, and beam search into a modular training and inference framework. The codebase showcased best practices for batching, bucketing by sequence length, and handling variable-length sequences efficiently on GPUs. Researchers used it as a baseline to reproduce classic results and to prototype new attention variants and training tricks. It also offered scripts for data preprocessing, evaluation, and exporting models for serving. ... -
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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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MITMf
Framework for Man-In-The-Middle attacks
MITMf aims to provide a one-stop-shop for Man-In-The-Middle and network attacks while updating and improving existing attacks and techniques. Originally built to address the significant shortcomings of other tools (e.g Ettercap, Mallory), it's been almost completely rewritten from scratch to provide a modular and easily extendible framework that anyone can use to implement their own MITM attack. The framework contains a built-in SMB, HTTP and DNS server that can be controlled and used by the various plugins, it also contains a modified version of the SSLStrip proxy that allows for HTTP modification and a partial HSTS bypass. As of version 0.9.8, MITMf supports active packet filtering and manipulation (basically what better filters did, only better), allowing users to modify any type of traffic or protocol. ... -
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z9
a simple client-server ERP system
z9 is a simple client-server ERP framework, based on a Python/PyQt modular smartclient and a PHP+SQL RESTful web service, created for the "opificio zeronove" bike shop application. -
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ElastAlert
Easy and flexible alerting with ElasticSearch
We designed ElastAlert to be reliable, highly modular, and easy to set up and configure. It works by combining Elasticsearch with two types of components, rule types and alerts. Elasticsearch is periodically queried and the data is passed to the rule type, which determines when a match is found. When a match occurs, it is given to one or more alerts, which take action based on the match. -
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Igorx
Modular Web-/Application server framework
Igorx is a modular Web-/Application server written in Python and C++. -
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sitecheck
Modular web site spider for web developers.
More than just a link checker, sitecheck is a website spider (also known as a crawler) which can assist with SEO by testing an entire site plus both inbound links from search engines and outbound links to other sites for the following issues: looping redirects (HTTP 301/302), broken links (HTTP 404), server errors (HTTP 500), spelling mistakes, low readability scores (using the Flesch Reading Ease test), missing/empty/duplicate meta tags, duplicate content, slow page speed, W3C validation... -
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BRAHMS is a Modular Execution Framework for dynamical systems. It knits together independently-authored software modules implementing dynamical processes into an integrated system, and supervises the deployment and execution of that system.
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GEPETTO - Gene Prioritization in Java
GEPETTO (GEne Prioritization ExTended TOol)
...It currently incorporates six prioritization modules, based on gene sequence, protein-protein interactions, gene expression, disease-causing probabilities, genomic context). GEPETTO is written in Java/Python and supported by an advanced modular architecture, which means that it can easily be modified and extended by the user, in order to include alternative scoring methods and new data sources. We intend to extend the system from gene-level to variant-level prioritization, by exploiting the variant data in the MSV3D database. Contact: bmhoan@gmail.com or walter.vincent.fr@gmail.com -
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SuperX
An Operating System based on the K Desktop Environment.
SuperX is a desktop-oriented computer operating system based on Ubuntu and Debian GNU/Linux, using the KDE desktop environment. It was originally developed in India by a teenager, Wrix who built it using free and open-source software. SuperX is highly modular, flexible and cloud-centric, with a desktop user interface especially designed with Linux beginners in mind. -
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Framework for making Windows applications that are one .exe file in AutoHotKey_L,C++,C#, VB.NET,Java,Groovy,Common Lisp,Nemerle,Ruby,Python,PHP,Lua,Tcl,Perl,Jint,S#,WSH VBScript,HTML/JavaScript/CSS,COM, PowerShell without compiling . For .NET 4.
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Universal Data Exchange server is a barebone modular server.
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BS Eagle Project is an open source black-oil simulator. The goal of this project is to provide a free access to the modern oil simulator to study new methods of simulation. The project has a modular architecture and open to modifications and extensions.
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PyHelper is a modular automatic documentation generator. Docs are generated directly from source code and can use different skins (python modules that render the documentation) to produce the doc-pages.
