Search Results for "mod-apache-snmp" - Page 5
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Showing 115 open source projects for "mod-apache-snmp"
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Graph Nets library
Build Graph Nets in Tensorflow
Graph Nets, developed by Google DeepMind, is a Python library designed for constructing and training graph neural networks (GNNs) using TensorFlow and Sonnet. It provides a high-level, flexible framework for building neural architectures that operate directly on graph-structured data. A graph network takes graphs as inputs, consisting of edges, nodes, and global attributes, and produces updated graphs with modified feature representations at each level. This library implements the... -
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PixieDust
Python Helper library for Jupyter Notebooks
PixieDust is an open source Python helper library that works as an add-on to Jupyter notebooks to improve the user experience of working with data. It also fills a gap for users who have no access to configuration files when a notebook is hosted on the cloud. -
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RecNN
Reinforced Recommendation toolkit built around pytorch 1.7
This is my school project. It focuses on Reinforcement Learning for personalized news recommendation. The main distinction is that it tries to solve online off-policy learning with dynamically generated item embeddings. I want to create a library with SOTA algorithms for reinforcement learning recommendation, providing the level of abstraction you like. -
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TF Quant Finance
High-performance TensorFlow library for quantitative finance
TF Quant Finance is a high-performance library of quantitative finance components built on TensorFlow, aimed at research and production workloads. It implements pricing engines, risk measures, stochastic models, optimizers, and random number generators that are differentiable and vectorized for accelerators. 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... -
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I3D models trained on Kinetics
Convolutional neural network model for video classification
Kinetics-I3D, developed by Google DeepMind, provides trained models and implementation code for the Inflated 3D ConvNet (I3D) architecture introduced in the paper “Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset” (CVPR 2017). The I3D model extends the 2D convolutional structure of Inception-v1 into 3D, allowing it to capture spatial and temporal information from videos for action recognition. This repository includes pretrained I3D models on the Kinetics dataset, with... -
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cnn-text-classification-tf
Convolutional Neural Network for Text Classification in Tensorflow
The cnn-text-classification-tf repository by Denny Britz is a well-known educational implementation of convolutional neural networks for text classification using TensorFlow, aimed at helping developers and researchers understand how CNNs can be applied to natural language processing tasks. Based loosely on Kim’s influential paper on CNNs for sentence classification, this codebase demonstrates how to preprocess text data, convert words into learned embeddings, and apply multiple convolution... -
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Compare GAN
Compare GAN code
compare_gan is a research codebase that standardizes how Generative Adversarial Networks are trained and evaluated so results are comparable across papers and datasets. It offers reference implementations for popular GAN architectures and losses, plus a consistent training harness to remove confounding differences in optimization or preprocessing. The library’s evaluation suite includes widely used metrics and diagnostics that quantify sample quality, diversity, and mode coverage. With... -
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Pyrlang
Erlang node implemented in Python 3.5+ (Asyncio-based)
This is a drop-in Erlang node implementation in Python 3, implementing a network Erlang node protocol. It was designed to allow interoperation between existing Python projects and BEAM languages: Erlang, Elixir, Gleam, Luaerl, LFE, Clojerl, and such. With just a few lines of startup code your Python program becomes an Erlang network node, participating in the Erlang cluster. -
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PrettyTensor
Pretty Tensor: Fluent Networks in TensorFlow
Pretty Tensor is a high-level API built on top of TensorFlow that simplifies the process of creating and managing deep learning models. It wraps TensorFlow tensors in a chainable object syntax, allowing developers to build multi-layer neural networks with concise and readable code. Pretty Tensor preserves full compatibility with TensorFlow’s core functionality while providing syntactic sugar for defining complex architectures such as convolutional and recurrent networks. The library’s design... -
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Switchboard
A feature flipper library for Pyramid and Pylons apps.
Switchboard is a port of Gargoyle, a feature flipper for Django apps, to the Pyramid or Pylons stack (including Turbogears). Originally used to selectively roll out changes to the SourceForge site, the library lets you easily control whether a particular change (a switch) is active. You can make switches active for a certain percentage of visitors, all visitors to a particular host in a cluster, or if a particular string is present in the query string. Furthermore you can easily create... -
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Question Answering Corpus
Question answering dataset in "Teaching Machines to Read & Comprehend"
RC-Data is a dataset generation framework created by Google DeepMind to produce large-scale reading comprehension question-answer pairs from CNN and Daily Mail news articles. The dataset, introduced in the 2015 paper “Teaching Machines to Read and Comprehend” (Hermann et al., NIPS 2015), was among the first large corpora designed to train and evaluate machine reading and comprehension models. The repository provides scripts for downloading archived CNN and Daily Mail articles from the... -
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Flask-AppBuilder
Rapid web application development (python + Flask)
Simple and rapid Application builder, built on top of Flask. includes detailed security, auto form generation, google charts and much more. Demo on: http://flaskappbuilder.pythonanywhere.com/ -
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z-utalm
Unified Test and Logging layer for multiple programming languages
Modern software systems and application are commonly written in multiple languages, include scripting engines, and are frequently build on multiple specialized frameworks and middleware for a considerable diversity of runtime environments. The latest influencing update in development paradigm is the application of multicore processors. This projects is aimed to unify the required trace and logging output and integrate into debugging environments. The target is to provide general development,... -
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Wootz
Various useful utils for SF.net
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