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bert-embedding

🔡 Token level embeddings from BERT model on mxnet and gluonnlp

doc2vec

:notebook: Long(er) text representation and classification using Doc2Vec embeddings

efficientnet

Implementation of EfficientNet model. Keras and TensorFlow Keras.

face_recognition

The world's simplest facial recognition api for Python and the command line

max-audio-embedding-generator

Generate embedding vectors from audio files

max-breast-cancer-mitosis-detector

Detect whether a mitosis exists in an image of breast cancer tumor cells

max-news-text-generator

Generate English-language text similar to the news articles in the One Billion Words data set.

max-text-sentiment-classifier

Detect the sentiment captured in short pieces of text

musicscoreclassifier

A python script that trains a model that can learn to distinguish between music scores and arbitrary content.

openl3

OpenL3: Open-source deep audio and image embeddings

pescador

Stochastic multi-stream sampling for iterative learning

pic2vec

Lightweight Image Featurization Made Easy

prince

:crown: Python factor analysis library (PCA, CA, MCA, MFA, FAMD)

pyalcs

Implementation of Anticipatory Learning Classifiers System (ALCS) in Python

pycoqc

pycoQC computes metrics and generates Interactive QC plots from the sequencing summary report generated by Oxford Nanopore technologies basecaller (Albacore/Guppy)

pylj

Teaching Utility for Classical Atomistic Simulation.

pynlpl

PyNLPl, pronounced as 'pineapple', is a Python library for Natural Language Processing. It contains various modules useful for common, and less common, NLP tasks. PyNLPl can be used for basic tasks such as the extraction of n-grams and frequency lists, and to build simple language model. There are also more complex data types and algorithms. Moreover, there are parsers for file formats common in NLP (e.g. FoLiA/Giza/Moses/ARPA/Timbl/CQL). There are also clients to interface with various NLP specific servers. PyNLPl most notably features a very extensive library for working with FoLiA XML (Format for Linguistic Annotation).

render-test-streamlit-iris

render-test-web-app

robot-surgery-segmentation

Wining solution and its improvement for MICCAI 2017 Robotic Instrument Segmentation Sub-Challenge

scattertext

Beautiful visualizations of how language differs among document types.

scikit-multilearn

A scikit-learn based module for multi-label et. al. classification

scikit-optimize

Sequential model-based optimization with a `scipy.optimize` interface

seglearn

Python module for machine learning time series:

sherpa

Hyperparameter optimization that enables researchers to experiment, visualize, and scale quickly.

soen6021-software-reengineering

Repo for SOEN 6021 course

soparallelcorpusreplication

Replication package for SO processing for bitext

timefhuman

Convert natural language date-like strings--dates, date ranges, and lists of dates--to Python objects

torchgpipe

A GPipe implementation in PyTorch

variability-ci-cd-ml

Studying the variablity in ML softwares due to CI practices