Race Recognition

In the first phase of this project, I analyzed the UTKFace dataset through the Pandas, Seaborn, and PyPlot libraries. Then, I prepared the data for the training process and trained an artificial neural network with the processed data using the Keras API. This model could predict each person's ethnicity by having their face image. Afterward, I tried to enhance the accuracy of predictions by changing different training parameters, such as the optimizer function or the kernel regularizer. In the last phase, I used the test data (30% of the dataset) to evaluate the model, which indicated an accuracy of 71%.