Search Results for "python-libpcap" - Page 5
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Showing 124 open source projects for "python-libpcap"
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Desktop and Mobile Device Management SoftwareDesktop Central is a unified endpoint management (UEM) solution that helps in managing servers, laptops, desktops, smartphones, and tablets from a central location.
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PyTorch Natural Language Processing
Basic Utilities for PyTorch Natural Language Processing (NLP)
PyTorch-NLP is a library for Natural Language Processing (NLP) in Python. It’s built with the very latest research in mind, and was designed from day one to support rapid prototyping. PyTorch-NLP comes with pre-trained embeddings, samplers, dataset loaders, metrics, neural network modules and text encoders. It’s open-source software, released under the BSD3 license. With your batch in hand, you can use PyTorch to develop and train your model using gradient descent. -
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InferSent
InferSent sentence embeddings
InferSent is a supervised sentence embedding method that learns universal representations from Natural Language Inference data and transfers well to many downstream tasks. It uses a BiLSTM encoder with max-pooling to produce fixed-length sentence vectors that capture semantics beyond bag-of-words statistics. Trained on large NLI datasets, the embeddings generalize across tasks like sentiment analysis, entailment, paraphrase detection, and semantic similarity with simple linear classifiers.... -
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Safe Harbor Deidentification
Safe Harbor Deidentification for medical documents
Phalanx - Deidentify Safe Harbor Deidentification Mode of Phalanx is an abridged pipeline of NLP annotators culminating in NER annotators which write output of text offsets. It uses the Safe Harbor deidentification method. -
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NeuroNER
Named-entity recognition using neural networks
Named-entity recognition (NER) aims at identifying entities of interest in the text, such as location, organization and temporal expression. Identified entities can be used in various downstream applications such as patient note de-identification and information extraction systems. They can also be used as features for machine learning systems for other natural language processing tasks. Leverages the state-of-the-art prediction capabilities of neural networks (a.k.a. "deep learning") Is... -
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lazynlp
Library to scrape and clean web pages to create massive datasets
LazyNLP is a lightweight tool for collecting and curating large-scale text datasets for machine learning and NLP applications with minimal manual effort. -
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TextRank
TextRank implementation for Python 3
TextRank is an implementation of the TextRank algorithm for extractive text summarization and keyword extraction, inspired by Google’s PageRank. -
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Arabic Corpus
Text categorization, arabic language processing, language modeling
The Arabic Corpus {compiled by Dr. Mourad Abbas ( http://sites.google.com/site/mouradabbas9/corpora ) The corpus Khaleej-2004 contains 5690 documents. It is divided to 4 topics (categories). The corpus Watan-2004 contains 20291 documents organized in 6 topics (categories). Researchers who use these two corpora would mention the two main references: (1) For Watan-2004 corpus ---------------------- M. Abbas, K. Smaili, D. Berkani, (2011) Evaluation of Topic Identification Methods on... -
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CRP - Chemical Reaction Prediction
Predicting Organic Reactions using Neural Networks.
The intend is to solve the forward-reaction prediction problem, where the reactants are known and the interest is in generating the reaction products using Deep learning. This Graphical User Interface takes simplified molecular-input line-entry system (SMILES) as an input and generates the product SMILE & molecule. Beam search is used in Version 2, to generate top 5 predictions. Maximum input length for the model is 15 (excluding spaces). -
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DeepLearn
Implementation of research papers on Deep Learning+ NLP+ CV in Python
Welcome to DeepLearn. This repository contains an implementation of the following research papers on NLP, CV, ML, and deep learning. The required dependencies are mentioned in requirement.txt. I will also use dl-text modules for preparing the datasets. If you haven't use it, please do have a quick look at it. CV, transfer learning, representation learning. -
Complete Data Management for NonprofitsNewOrg is a robust platform built with enhanced features to help non-profit organizations that capture and integrate the information from all of their operational areas to better manage volunteers, clients, programs, outcome reporting, activity sign-ups & scheduling, communications, surveys, fundraising activities and Development campaigns. NewOrg can truly deliver an intuitive product that will help manage your Committees, Donors, Events, and Memberships so that the organization runs efficiently.
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AI learning
AiLearning, data analysis plus machine learning practice
We actively respond to the Research Open Source Initiative (DOCX) . Open source today is not just open source, but datasets, models, tutorials, and experimental records. We are also exploring other categories of open source solutions and protocols. I hope you will understand this initiative, combine this initiative with your own interests, and do what you can. Everyone's tiny contributions, together, are the entire open source ecosystem. We are iBooker, a large open-source community,... -
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Seq2Seq Chatbot
Chatbot in 200 lines of code using TensorLayer
Seq2Seq Chatbot is an implementation of a sequence-to-sequence chatbot model using TensorLayer, demonstrating how to build conversational agents with minimal code. -
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Seq2seq Chatbot for Keras
This repository contains a new generative model of chatbot
This repository contains a new generative model of chatbot based on seq2seq modeling. The trained model available here used a small dataset composed of ~8K pairs of context (the last two utterances of the dialogue up to the current point) and respective response. The data were collected from dialogues of English courses online. This trained model can be fine-tuned using a closed-domain dataset to real-world applications. The canonical seq2seq model became popular in neural machine... -
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TEES
Turku Event Extraction System
Turku Event Extraction System (TEES) is a free and open source natural language processing system developed for the extraction of events and relations from biomedical text. It is written mostly in Python, and should work in generic Unix/Linux environments. Currently, the TEES source code repository still remains on GitHub at http://jbjorne.github.com/TEES/ where there is also a wiki with more information. -
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GT NLP Class
Course materials for Georgia Tech CS 4650 and 7650
...Students work through programming exercises and problem sets that build intuition for both classical algorithms (like HMMs and CRFs) and neural approaches (like word embeddings and sequence models). The materials emphasize theory grounded in practical experimentation, often via Python notebooks or scripts that visualize results and encourage ablation studies. Clear organization and self-contained examples make it possible to follow along outside the classroom, using the repo as a self-study resource. For learners and instructors alike, the course provides a coherent path from foundational linguistics to current techniques, with reproducible code that makes concepts concrete. -
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BioC
We describe a simple XML format to share text documents and annotation
A minimalist approach to share text documents and data annotations. Allows a large number of different annotations to be represented. Project files contain: - simple code to hold/read/write data and perform sample processing. - BioC-formatted corpora - BioC tools that work with BioC corpora BioC goals - simplicity - interoperability - broad use - reuse There should be little investment required to learn to use a format or a software module to process that format. We are... -
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VADER
Lexicon and rule-based sentiment analysis tool
VADER (Valence Aware Dictionary and sEntiment Reasoner) is a lexicon and rule-based sentiment analysis tool designed for analyzing the sentiment of text, particularly in social media and short text formats. It is optimized for quick and accurate analysis of positive, negative, and neutral sentiments. -
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tnets
Theano-based (Deep) Neural Networks for Speech Research
Alpha tool build on the top of Theano and delibaretly tuned for ASR/NLP tasks. -
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TextBlob
TextBlob is a Python library for processing textual data
Simple, Pythonic, text processing, Sentiment analysis, part-of-speech tagging, noun phrase extraction, translation, and more. It provides a simple API for diving into common natural language processing (NLP) tasks such as part-of-speech tagging, noun phrase extraction, sentiment analysis, classification, translation, and more. TextBlob stands on the giant shoulders of NLTK and pattern, and plays nicely with both. Supports word inflection (pluralization and singularization) and lemmatization,... -
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Redundancy due to cut-paste operations in text creates bias in machine learning for NLP. This module takes a directory and produces a subset of the files in that directory (in a list) with an upper bound on similarity between two files.
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Sylli is a universal syllabifier. Developed for Italian, it can easily be adapted to any language that is claimed to respect the SSP. Sylli divides timit, strings, files and directories into syllables.
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MutationFinder is a biomedical natural language processing (NLP) system for extracting mentions of point mutations from free text. MutationFinder achieves high performance (99% precision, 81% recall on blind test data) as an information extraction system
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Cathnet is developing the infrastructure for the Catholic Semantic Web. Technologies involved include, but are not limited to, XML, RDF, NLP, Zope, Plone and Plone products.
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Collection of Python scripts providing interactions between the sociological investigation platform and webservices (such as NLP, search engine, web database).
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webXcreta users natural language processing to create grammatical averages of textual communication and then generate original content based on these statistics.
