Search Results for "mac framework" - Page 38
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Showing 1357 open source projects for "mac framework"
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hug
Embrace the APIs of the future. For developing APIs
hug aims to make developing Python-driven APIs as simple as possible, but no simpler. As a result, it drastically simplifies Python API development. Make developing a Python-driven API as succinct as a written definition. The framework should encourage code that self-documents. It should be fast. A developer should never feel the need to look somewhere else for performance reasons. Writing tests for APIs written on-top of hug should be easy and intuitive. Magic done once, in an API... -
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Neural MMO
Code for the paper "Neural MMO: A Massively Multiagent Game..."
Neural MMO is a massively multi-agent simulation environment developed by OpenAI for reinforcement learning research. It provides a persistent, procedurally generated world where thousands of agents can interact, compete, and cooperate in real time. The environment is inspired by Massively Multiplayer Online Role-Playing Games (MMORPGs), featuring resource gathering, combat mechanics, exploration, and survival challenges. Agents learn behaviors in a shared ecosystem that supports long-term... -
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MMF
A modular framework for vision & language multimodal research
MMF is a modular framework for vision and language multimodal research from Facebook AI Research. MMF contains reference implementations of state-of-the-art vision and language models and has powered multiple research projects at Facebook AI Research. MMF is designed from ground up to let you focus on what matters, your model, by providing boilerplate code for distributed training, common datasets and state-of-the-art pre-trained baselines out-of-the-box. MMF is built on top of PyTorch that... -
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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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CCZero (中国象棋Zero)
Implement AlphaZero/AlphaGo Zero methods on Chinese chess
ChineseChess-AlphaZero is a project that implements the AlphaZero algorithm for the game of Chinese Chess (Xiangqi). It adapts DeepMind’s AlphaZero method—combining neural networks and Monte Carlo Tree Search (MCTS)—to learn and play Chinese Chess without prior human data. The system includes self-play, training, and evaluation pipelines tailored to Xiangqi's unique game mechanics. -
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Olex2 is visualisation software for small-molecule crystallography developed at Durham University/EPSRC. It provides comprehensive tools for crystallographic model manipulation for the end user and an extensible development framework for programmers. The project has been supported by Olexsys Ltd since 2010.
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A symbolic framework for C++, Python and Octave implementing automatic differentiation by source code transformation in forward and reverse modes on sparse matrix-valued computational graphs.
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AIAlpha
Use unsupervised and supervised learning to predict stocks
AIAlpha is a machine learning project focused on building predictive models for financial markets and algorithmic trading strategies. The repository explores how artificial intelligence techniques can analyze historical financial data and generate predictions about asset price movements. It provides a research-oriented environment where users can experiment with data processing pipelines, model training workflows, and quantitative trading strategies. The project typically involves collecting... -
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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... -
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maskrcnn-benchmark
Fast, modular reference implementation of Instance Segmentation
Mask R-CNN Benchmark is a PyTorch-based framework that provides high-performance implementations of object detection, instance segmentation, and keypoint detection models. Originally built to benchmark Mask R-CNN and related models, it offers a clean, modular design to train and evaluate detection systems efficiently on standard datasets like COCO. The framework integrates critical components—region proposal networks (RPNs), RoIAlign layers, mask heads, and backbone architectures such as... -
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vid2vid
Pytorch implementation of our method for high-resolution
vid2vid is a deep learning framework for high-resolution video-to-video translation that generates photorealistic videos from structured inputs such as semantic maps, pose sequences, or edge maps. Built on top of image-to-image translation techniques like pix2pixHD, it extends these ideas into the temporal domain by ensuring consistency across video frames. The system can synthesize complex outputs such as realistic talking faces, human motion animations, or dynamic street scenes by learning... -
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backtrader
Python Backtesting library for trading strategies
backtrader is a Python framework for developing, backtesting, and running trading strategies. Its Cerebro engine coordinates strategies, data feeds, brokers, indicators, analyzers, and execution. Developers can combine multiple strategies, instruments, and timeframes while resampling or replaying market data. The framework includes a large indicator library, custom indicator support, analyzers, position sizing, commissions, and trading calendars. Its broker simulation supports market, limit,... -
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TestLink-API-Python-client
Python XML-RPC client for TestLink
TestLink-API-Python-client is a Python XML-RPC client for TestLink Initially based on James Stock testlink-api-python-client R7 and Olivier Renault JinFeng idea - an interaction of TestLink, Robot Framework and Jenkins. TestLink-API-Python-client delivers two main classes - TestlinkAPIGeneric - Implements the Testlink API methods as generic PY methods with error handling - TestlinkAPIClient - Inherits from TestlinkAPIGeneric and defines service methods like "copyTCnewVersion" and... -
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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... -
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Offensive Web Testing Framework
Offensive Web Testing Framework (OWTF), is a framework
OWASP OWTF is a project focused on penetration testing efficiency and alignment of security tests to security standards like the OWASP Testing Guide (v3 and v4), the OWASP Top 10, PTES and NIST so that pentesters will have more time to see the big picture and think out of the box. More efficiently find, verify and combine vulnerabilities. Have time to investigate complex vulnerabilities like business logic/architectural flaws or virtual hosting sessions. Perform more tactical/targeted... -
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MUSE
A library for Multilingual Unsupervised or Supervised word Embeddings
MUSE is a framework for learning multilingual word embeddings that live in a shared space, enabling bilingual lexicon induction, cross-lingual retrieval, and zero-shot transfer. It supports both supervised alignment with seed dictionaries and unsupervised alignment that starts without parallel data by using adversarial initialization followed by Procrustes refinement. The code can align pre-trained monolingual embeddings (such as fastText) across dozens of languages and provides standardized... -
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Rasa Core
Rasa Core is now part of the Rasa repo
Rasa is an open source machine learning framework to automate text and voice-based conversations. With Rasa, you can build contextual assistants. Rasa helps you build contextual assistants capable of having layered conversations with lots of back-and-forth. In order for a human to have a meaningful exchange with a contextual assistant, the assistant needs to be able to use context to build on things that were previously discussed – Rasa enables you to build assistants that can do this in a... -
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Django REST Pandas
Serves up Pandas dataframes via the Django REST Framework
Django REST Pandas (DRP) provides a simple way to generate and serve pandas DataFrames via the Django REST Framework. The resulting API can serve up CSV (and a number of other formats for consumption by a client-side visualization tool like d3.js. The design philosophy of DRP enforces a strict separation between data and presentation. This keeps the implementation simple, but also has the nice side effect of making it trivial to provide the source data for your visualizations. This... -
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automl-gs
Provide an input CSV and a target field to predict, generate a model
Give an input CSV file and a target field you want to predict to automl-gs, and get a trained high-performing machine learning or deep learning model plus native Python code pipelines allowing you to integrate that model into any prediction workflow. No black box: you can see exactly how the data is processed, and how the model is constructed, and you can make tweaks as necessary. automl-gs is an AutoML tool which, unlike Microsoft's NNI, Uber's Ludwig, and TPOT, offers a zero code/model... -
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Invenio
Invenio digital library framework
Invenio is a highly customizable open-source framework for building large-scale digital repositories and research data platforms. 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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ShadowSocksShare
Python ShadowSocks framework
This project obtains the shared ss(r) account from the ss(r) shared website crawler, redistributes the account and generates a subscription link by parsing and verifying the account connectivity. Since Google plus will be closed on April 2, 2019, almost all the available accounts crawled before come from Google plus. So if you are building your own website, please keep an eye on the updates of this project and redeploy using the latest source code. -
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PythonQt
Dynamic Python binding for Qt Applications
NOTE: PythonQt has been moved to https://github.com/MeVisLab/pythonqt PythonQt is a dynamic and lightweight script binding of the Qt framework to the Python language. It can be easily embedded into Qt applications and makes any QObject derived object scriptable via Python without the need of wrapper code generation. -
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django-dynamic-scraper
Creating Scrapy scrapers via the Django admin interface
Django Dynamic Scraper (DDS) is an app for Django build on top of the scraping framework Scrapy. While preserving many of the features of Scrapy it lets you dynamically create and manage spiders via the Django admin interface. With Django Dynamic Scraper (DDS) you can define your Scrapy scrapers dynamically via the Django admin interface and save your scraped items in the database you defined for your Django project. Since it simplifies things DDS is not usable for all kinds of scrapers, but... -
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PySys is a Python based framework for the organisation and execution of system level automated and manual testcases. PROJECT MOVED: As of April 2019, PySys has moved to GitHub and is no longer maintained on SourceForge, so for the development project go to https://github.com/pysys-test/pysys-test or for end-users of PySys go to https://pypi.org/project/PySys/
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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...
