There are 1 repository under ethnicity-classifier topic.
NamSor API v2 Python SDK - classify personal names accurately by gender, country of origin, or ethnicity.
NamSor Python command line tools, to append gender, origin, diaspora or us 'race'/ethnicity to a CSV file.
This repository contains a console-interface name-ethnicity classifier
NamSor API v2 R SDK - classify personal names accurately by gender, country of origin, or ethnicity.
predict ethnicity from names
Experimental tagging schema for analysis of intersectionality, bias, and reception theories.
Tensorflow Keras based pre-trained model to predict gender and ethnicity of Indian Names using Python
NamSor API v2 Java SDK - classify personal names accurately by gender, country of origin, or ethnicity.
NamSor API v2 Java SDK - classify personal names accurately by gender, country of origin, or ethnicity.
NamSor command line tools, to append gender, origin, diaspora or us 'race'/ethnicity to a CSV file.
EthnicityPredictor-UTK is a PyTorch-based project that focuses on predicting ethnicities from facial images using state-of-the-art ResNet architectures. Leveraging the UTKfaces dataset, the model is trained to recognize diverse facial features and make accurate ethnicity predictions.
NamSor Salesforce Add-on : append likely gender to your SFSC / CRM contacts automatically. Can easily be forked to append US race / ethnicity, or country of origin as well.
A simple program using Resnet, Transfer Learning, Metric Learning and KNN-Classifiers to predict the ethnicity of a person using their images.
This classifier uses the sub-strings of size 3 to learn probability associated with each substring such that it belongs to a particular ethnic group using the census 2000 data. When a new string is presented, it is broken down into sub-strings of size 3, and prediction is done on each of the sub-string using the model computed before. The output accuracy of the predictor is 85%. The model can be improved by balancing the sub-strings and the across the ethnic groups. The model follows the Naive Bayes assumption of conditional independence
A pipeline utilizing PCA on 1000 genomes and WGS data from your own samples to determine or validate ancestry of an individual.
Your name contains a lot of information. It tells if you're male or female and reveals your nationality. This project splits a name or email address into the first and last name and tells if a name is male or female and what the possible nationality is. Additionally this project can generate fake names and extract names from any given text.
Your name contains a lot of information. It tells if you're male or female and reveals your nationality. This project splits a name or email address into the first and last name and tells if a name is male or female and what the possible nationality is. Additionally this project can generate fake names and extract names from any given text.
Implementation for paper, "Learned Features are better for Ethnicity classification"
NamSor API v2 Ruby SDK - classify personal names accurately by gender, country of origin, or ethnicity.
LSTM ethnicity classifier from names, based on wikipedia data
Classifies among three ethnic groups : Indian, African and Chinese ethnicity.
Final Project of Data Science & Algorithm Course