In this article, I’ll walk you through a machine learning project on gender classification with the Python programming language.
Gender classification is essential and critical for many applications in business fields such as human-computer interaction applications and computer-aided physiological or psychological analysis, as it contains a wide range of information regarding the difference of characteristics between man and woman.
Introduction to Gender Classification
The Gender classification is gaining more and more attention, as gender contains rich and distinguished information about the social activities of men and women. Gender classification aims to recognize a person’s gender based on the characteristics that differentiate masculinity and femininity.
In the field of artificial intelligence, gender classification is considered to be one of the most important applications of the pattern recognition method. Advances in gender classification research have led to many potential applications.
For example, a computer system with gender recognition functions has a wide range of applications in the fields of basic and applied research, including human-computer interaction, security industry and surveillance, demographic research, business development, mobile applications and video games.
Also, multiple mechanisms are proposed to improve the performance of gender recognition in terms of accuracy and efficiency.
Machine Learning Project on Gender Classification with Python
Now, in this section, I will take you through a Machine Learning project on Gender Classification with Python. Let’s get started with this task by importing the necessary Python libraries:
Now let’s read and import the images dataset that we are going to use to train a neural network model:
Now we need to train and compile the neural network model for the task of Gender classification with Python:
Before testing this model let’s have a look at how the model performs in terms of accuracy:
Now let’s test our neural network model in both the cases of male and female:
[0.] is a female
In the above output, we can see that the model performs very well. I hope you liked this article on Gender Classification with Python programming language. Feel free to ask your valuable questions in the comments section below.