This article discusses various types of machine learning classifiers, including their technical implementation, data types, techniques, and limitations. It also explores different technologies such as TensorFlow, PyTorch, Scikit-learn, and Armadillo for building classifiers, and highlights the importance of understanding the classification objective to limit the scope of a classifier. Additionally, it touches upon the use of Long Short Term Memory (LSTM) neural networks, Transformers, Conditional Generative Adversarial Networks, and Convolutional Recurrent Neural Networks in classifying text, audio, and video data. Furthermore, it introduces Symbl.ai as a conversational intelligence platform that simplifies classifying audio and video data by offering pre-trained machine learning models and APIs for easy integration with applications.