Deep Learning-based Age and Gender Detection

The book "Age and Gender Detection by Python" offers a thorough exploration of age and gender detection methods using Python. It covers fundamental concepts, challenges, and various algorithms like SVM, Random Forests, CNNs, and RNNs. Advanced topics include transfer learning, ensemble methods, and ethical considerations. Practical guidance is provided with coding examples using libraries like OpenCV, scikit-learn, TensorFlow, and Keras. Real-world applications demonstrate the relevance of the discussed techniques. Readers gain expertise in building age and gender recognition systems, benefiting fields like social sciences, marketing, and biometrics.

Autorentext

Mazin Riyadh AL-Hmeed is Assistant Lecturer in National University of Science and Technology, Iraq. PhD in Information Technology at Alexandria University, Egypt. MSc in Computer Science at Modern University for Business and Science, Lebanon.Fatima Asaad Mohhammed is Research Assistant National University of Science and Technology.

Klappentext

The book "Age and Gender Detection by Python" offers a thorough exploration of age and gender detection methods using Python. It covers fundamental concepts, challenges, and various algorithms like SVM, Random Forests, CNNs, and RNNs. Advanced topics include transfer learning, ensemble methods, and ethical considerations. Practical guidance is provided with coding examples using libraries like OpenCV, scikit-learn, TensorFlow, and Keras. Real-world applications demonstrate the relevance of the discussed techniques. Readers gain expertise in building age and gender recognition systems, benefiting fields like social sciences, marketing, and biometrics.