Search Results for "gcc-core" - Page 3
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Showing 256 open source projects for "gcc-core"
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Ray
A unified framework for scalable computing
Modern workloads like deep learning and hyperparameter tuning are compute-intensive and require distributed or parallel execution. Ray makes it effortless to parallelize single machine code — go from a single CPU to multi-core, multi-GPU or multi-node with minimal code changes. Accelerate your PyTorch and Tensorflow workload with a more resource-efficient and flexible distributed execution framework powered by Ray. Accelerate your hyperparameter search workloads with Ray Tune. Find the best... -
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aws-encryption-sdk
AWS Encryption SDK
The AWS Encryption SDK is a client-side encryption library designed to make it easy for everyone to encrypt and decrypt data using industry standards and best practices. It enables you to focus on the core functionality of your application, rather than on how to best encrypt and decrypt your data. The AWS Encryption SDK is provided free of charge under the Apache 2.0 license. With the AWS Encryption SDK, you define a master key provider (Java and Python) or a keyring (C, C#/.NET, and JavaScript... -
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NuPIC
Numenta platform for intelligent computing
The Numenta Platform for Intelligent Computing (NuPIC) is a machine intelligence platform that implements the HTM learning algorithms. HTM is a detailed computational theory of the neocortex. 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... -
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Optax
Optax is a gradient processing and optimization library for JAX
Optax is a gradient processing and optimization library for JAX. It is designed to facilitate research by providing building blocks that can be recombined in custom ways in order to optimize parametric models such as, but not limited to, deep neural networks. We favor focusing on small composable building blocks that can be effectively combined into custom solutions. Others may build upon these basic components in more complicated abstractions. Whenever reasonable, implementations prioritize... -
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EconML
Python Package for ML-Based Heterogeneous Treatment Effects Estimation
EconML is a Python package for estimating heterogeneous treatment effects from observational data via machine learning. This package was designed and built as part of the ALICE project at Microsoft Research with the goal of combining state-of-the-art machine learning techniques with econometrics to bring automation to complex causal inference problems. One of the biggest promises of machine learning is to automate decision-making in a multitude of domains. At the core of many data-driven... -
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gensim
Topic Modelling for Humans
Gensim is a Python library for topic modeling, document indexing, and similarity retrieval with large corpora. The target audience is the natural language processing (NLP) and information retrieval (IR) community. -
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mistletoe
A fast, extensible and spec-compliant Markdown parser in pure Python
mistletoe is a Markdown parser in pure Python, designed to be fast, spec-compliant and fully customizable. Apart from being the fastest CommonMark-compliant Markdown parser implementation in pure Python, mistletoe also supports easy definitions of custom tokens. Parsing Markdown into an abstract syntax tree also allows us to swap out renderers for different output formats, without touching any of the core components. -
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Emissary-ingress
open source Kubernetes-native API gateway for microservices
Emissary-Ingress is the most popular API Gateway Kubernetes-native - open-source, that delivers scalability, flexibility, and simplicity for some of the world's largest Kubernetes installations. Emissary-Ingress is an open source CNCF incubating project, and it uses the ubiquitous Envoy Proxy at its core. Once your organization hits a certain scale, a reverse proxy or load balancer isn’t enough for traffic management. If you’re using Kubernetes, you’re probably already at that scale and need... -
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BlackSheep
Fast ASGI web framework for Python
BlackSheep is an asynchronous web framework to build event-based web applications with Python. A rich code API, based on dependency injection and inspired by Flask and ASP.NET Core. A typing-friendly codebase, which enables a comfortable development experience thanks to hints when coding with IDEs. Built-in generation of OpenAPI Documentation, supporting version 3, YAML, and JSON. A cross-platform framework, using the most modern versions of Python. BlackSheep supports automatic binding... -
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Django Ninja
Fast, Async-ready, Openapi, type hints based framework
Django Ninja is a web framework for building APIs with Django and Python 3.6+ type hints. Designed to be easy to use and intuitive. Very high performance thanks to Pydantic and async support. Type hints and automatic docs lets you focus only on business logic. Based on the open standards for APIs: OpenAPI (previously known as Swagger) and JSON Schema. Django friendly (obviously) has good integration with the Django core and ORM. Used by multiple companies on live projects. -
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Mercury
Convert Python notebook to web app and share with non-technical users
Turn Python notebooks to web applications with open-source Mercury framework. Hide code and add interactive widgets. Non-technical users can tweak widgets and execute notebook with new parameters. The core of Mercury is Open Source under AGPLv3. We provide Mercury Pro with additional features, dedicated support and friendly commercial license. Mercury is a perfect tool to convert Python notebook to interactive web application and share with non-programmers. You define interactive widgets... -
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Ajenti 2
Ajenti Core and stock plugins
Ajenti is a Linux & BSD modular server admin panel. Ajenti 2 provides a new interface and a better architecture, developed with Python3 and AngularJS. Ajenti 2 can be easily installed with pip and the provided script. Picks up your current configuration and works on your existing system as-is, without any preparation. Does not overwrite your config files, options and comments. All changes are non-destructive. Includes lots of plugins for system and software configuration, monitoring and... -
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Dshell
Dshell is a network forensic analysis framework
... plugins without overlapping the core Dshell libraries. Plugins can now use all output modules, available to the command line switch, -O. That does not mean every output module will be useful to every plugin (e.g. using netflow output for a plugin that looks at individual packets), but they are available. -
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CuPy
A NumPy-compatible array library accelerated by CUDA
CuPy is an open source implementation of NumPy-compatible multi-dimensional array accelerated with NVIDIA CUDA. It consists of cupy.ndarray, a core multi-dimensional array class and many functions on it. CuPy offers GPU accelerated computing with Python, using CUDA-related libraries to fully utilize the GPU architecture. According to benchmarks, it can even speed up some operations by more than 100X. CuPy is highly compatible with NumPy, serving as a drop-in replacement in most cases... -
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Pyro
Deep universal probabilistic programming with Python and PyTorch
Pyro is a flexible, universal probabilistic programming language (PPL) built on PyTorch. It allows for expressive deep probabilistic modeling, combining the best of modern deep learning and Bayesian modeling. Pyro is centered on four main principles: Universal, Scalable, Minimal and Flexible. Pyro is universal in that it can represent any computable probability distribution. It scales easily to large datasets with minimal overhead, and has a small yet powerful core of composable abstractions... -
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snorkel
A system for quickly generating training data with weak supervision
The Snorkel team is now focusing their efforts on Snorkel Flow, an end-to-end AI application development platform based on the core ideas behind Snorkel. The Snorkel project started at Stanford in 2016 with a simple technical bet: that it would increasingly be the training data, not the models, algorithms, or infrastructure, that decided whether a machine learning project succeeded or failed. Given this premise, we set out to explore the radical idea that you could bring mathematical... -
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Jupyter Enterprise Gateway
Enables Jupyter Notebooks to share resources across clusters
Jupyter Enterprise Gateway is a headless web server with a pluggable framework for anyone supporting multiple notebook users in a managed-cluster environment. Some of the core functionality it provides is better optimization of compute resources, improved multi-user support, and more granular security for your Jupyter notebook environment - making it suitable for enterprise, scientific, and academic implementations. From a technical perspective, Jupyter Enterprise Gateway is a web server... -
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Chameleon LLM
Codes for "Chameleon: Plug-and-Play Compositional Reasoning
Discover Chameleon, our cutting-edge compositional reasoning framework designed to enhance large language models (LLMs) and overcome their inherent limitations, such as outdated information and lack of precise reasoning. By integrating various tools such as vision models, web search engines, Python functions, and rule-based modules, Chameleon delivers more accurate, up-to-date, and precise responses, making it a game-changer in the natural language processing landscape. With GPT-4 at its core... -
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whylogs
The open standard for data logging
whylogs is an open-source library for logging any kind of data. With whylogs, users are able to generate summaries of their datasets (called whylogs profiles) which they can use to track changes in their dataset Create data constraints to know whether their data looks the way it should. Quickly visualize key summary statistics about their datasets. whylogs profiles are the core of the whylogs library. They capture key statistical properties of data, such as the distribution (far beyond simple... -
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PaddleNLP
Easy-to-use and powerful NLP library with Awesome model zoo
PaddleNLP It is a natural language processing development library for flying paddles, with Easy-to-use text area API, Examples of applications for multiple scenarios, and High-performance distributed training Three major features, aimed at improving the modeling efficiency of the flying oar developer's text field, aiming to improve the developer's development efficiency in the text field, and provide rich examples of NLP applications. Provide rich industry-level pre-task capabilities... -
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Django Rules
Awesome Django authorization, without the database
rules is a tiny but powerful app providing object-level permissions to Django, without requiring a database. At its core, it is a generic framework for building rule-based systems, similar to decision trees. It can also be used as a standalone library in other contexts and frameworks. Versatile. Decorate callables to build complex graphs of predicates. Predicates can be any type of callable -- simple functions, lambdas, methods, callable class objects, partial functions, decorated functions... -
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Graphene-Django
Integrate GraphQL into your Django project
Graphene-Django is built on top of Graphene. Graphene-Django provides some additional abstractions that make it easy to add GraphQL functionality to your Django project. First time? We recommend you start with the installation guide to get set up and the basic tutorial. It is worth reading the core graphene docs to familiarize yourself with the basic utilities. Graphene Django has a number of additional features that are designed to make working with Django easy. Our primary focus... -
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PaddleX
PaddlePaddle End-to-End Development Toolkit
PaddleX is a deep learning full-process development tool based on the core framework, development kit, and tool components of Paddle. It has three characteristics opening up the whole process, integrating industrial practice, and being easy to use and integrate. Image classification and labeling is the most basic and simplest labeling task. Users only need to put pictures belonging to the same category in the same folder. When the model is trained, we need to divide the training set... -
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Raster Vision
Open source framework for deep learning satellite and aerial imagery
Raster Vision is an open source framework for Python developers building computer vision models on satellite, aerial, and other large imagery sets (including oblique drone imagery). There is built-in support for chip classification, object detection, and semantic segmentation using PyTorch. Raster Vision allows engineers to quickly and repeatably configure pipelines that go through core components of a machine learning workflow: analyzing training data, creating training chips, training models... -
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Lightly
A python library for self-supervised learning on images
A python library for self-supervised learning on images. We, at Lightly, are passionate engineers who want to make deep learning more efficient. That's why - together with our community - we want to popularize the use of self-supervised methods to understand and curate raw image data. Our solution can be applied before any data annotation step and the learned representations can be used to visualize and analyze datasets. This allows selecting the best core set of samples for model training...