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AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet.
Detect common phrases in large amounts of text using a data-driven approach. Size of discovered phrases can be arbitrary. Can be used in languages other than English
Convenience Docker images for Apache Tika Server
[ACL 2021] Code for our ACL 2021 paper "One2Set: Generating Diverse Keyphrases as a Set"
Data for Automatic Keyphrase Extraction Task
Multilingual Sentence & Image Embeddings with BERT
Use BERT to train a classification model and deploy the model by tensorflow serving
A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning
Daily time-series epidemiology and hospitalization data for all countries, state/province data for 50+ countries and county/municipality data for CO, FR, NL, PH, UK and US. Covariates for all avail…
A customizable plug-in photo gallery management application for the Django web framework.
A collection of corpora for named entity recognition (NER) and entity recognition tasks. These annotated datasets cover a variety of languages, domains and entity types.
A system for quickly generating training data with weak supervision
Implementation of various string similarity and distance algorithms: Levenshtein, Jaro-winkler, n-Gram, Q-Gram, Jaccard index, Longest Common Subsequence edit distance, cosine similarity ...
Language, engine, and tooling for expressing, testing, and evaluating composable language rules on input strings.
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
Voice activity detection (VAD) toolkit including DNN, bDNN, LSTM and ACAM based VAD. We also provide our directly recorded dataset.
Deep neural network based speech enhancement toolkit
Removing background noise in a sound file
Python interface to the WebRTC Voice Activity Detector
Models and examples built with TensorFlow
In this repository, I will share some useful notes and references about deploying deep learning-based models in production.
Deep learning with PyTorch, published by Packt
AmbiverseNLU: A Natural Language Understanding suite by Max Planck Institute for Informatics
Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.
A fast, extensible, transparent python library for backtesting quantitative strategies.
A text tagger based on Lucene / Solr, using FST technology