Gender Recognizer

The aim of the paper is to choose the best gender classification Machine Learning model between Logistic Regression, SVM, Random Forest and Adaptive Boost algorithms.

How to run the demo

To run the code you need to install Python Anaconda distribution or to install the following dependencies:

• jupyter (Jupyter Notebook)
• opencv-python (you can skip this and to install later from the Jupyter Notebook)
• matplotlib
• pandas
• scikit-learn

For Anaconda users

I do not recommend the opencv that comes with Anaconda distribution. Currently it does not work perfect with Jupyter and maybe you will not be able to run the code or the demo without errors (although when reading this the problem may be resolved).

To remove opencv from Anaconda you can use: conda remove --yes opencv