Introduction to Sequence Modeling Problems

Consider the problem of predicting the health risk of a person based on multiple health parameters and we have decided to model the true relationship between the input and output using Feed-forward neural networks (also known as Multi-layered Network of Neurons). In Feed-forward Neural Networks (FNN) the output of one data point is completely independent of the previous input i.e… the health risk of the second person is not dependent on the health risk of the first person and so on. Similarly, in the case of Convolution Neural Networks (CNN), the output from the softmax layer in the context of image classification is entirely independent of the previous input image. Citation Note: The content and the structure of this article is based my understand of the deep learning lectures from One-Fourth Labs -- PadhAI. Sequence Modeling is the task of predicting what word/letter comes next. Unlike the FNN and CNN, in sequence modeling, the current output is dependent on the previous input and the length of the input is not fixed.