Predicting Gender by First Name Using Character-level Machine Learning

We classified the gender of Brazilian names using deep learning and machine learning. See the document here.

Download the dataset

    url = "https://data.brasil.io/dataset/genero-nomes/nomes.csv.gz"
    filename = url.split("/")[-1]
    with open(filename, "wb") as f:
        r = requests.get(url)
        f.write(r.content)

Deep learning models

Models: , , , , .

Usage is simple.

    testename = prepare_encod_names({"cibely"})   # name are encod as a vector of numbers
    resu=(LSTMmodel.predict(testename) > 0.5).astype("int32")
    if int(resu)==1:
      print('M')
    else:
      print('F')
      
    out: F

Papers

R. C. B. Rego, G. d. S. Nascimento, D. E. d. L. Rodrigues, S. M. Nascimento and V. M. L. Silva, "Brazilian scientific productivity from a gender perspective during the Covid-19 pandemic: classification and analysis via machine learning," in IEEE Latin America Transactions, vol. 21, no. 2, pp. 302-309, Feb. 2023, doi: 10.1109/TLA.2023.10015223.

Rego, R. C., Silva, V. M. & Fernandes, V. M. (2021). Predicting Gender by First Name Using Character-level Machine Learning. arXiv preprint arXiv:2106.10156 v2.

Rego, R. C., & Silva, V. M. (2021). Predicting gender of Brazilian names using deep learning. arXiv preprint arXiv:2106.10156 v1.