Deep Learning-Inspired Multiclass and Multi-label Classifications

This chapter explores deep learning approaches to multiclass and multilabel classification, providing a comprehensive overview of advanced techniques. We begin with multiclass classification using ‘Multilayer Perceptron (MLP)’ and then delve into more sophisticated methods, including ‘Convolutional Neural Networks (CNNs)’ and ‘Recurrent Neural Networks (RNNs)’. This chapter also covers innovative approaches using ‘Deep Generative Networks’, such as ‘Generative Adversarial Networks (GANs)’, and ‘Transfer Learning’. Readers will gain both theoretical insights and practical experience through hands-on coding examples, equipping them with the skills to implement deep learning models for complex classification tasks.