A Must-Read Introduction to Sequence Modelling (with use cases)

Introduction

Artificial Neural Networks (ANN) were supposed to replicate the architecture of the human brain, yet till about a decade ago, the only common feature between ANN and our brain was the nomenclature of their entities (for instance – neuron). These neural networks were almost useless as they had very low predictive power and less number of practical applications.

But thanks to the rapid advancement in technology in the last decade, we have seen the gap being bridged to the extent that these ANN architectures have become extremely useful across industries.

In this article, we will look at the two main advances in the field of artificial neural networks that have made these ANNs more like the human brain,

Table of Contents

1. Two Main Advances in the Field of ANN
2. Thought Experiment
3. Practical Applications of Sequence Modelling
4. Sequence Generators
5. Sequence to Sequence NLP Models
6. Few More

    

    

    

   To finish reading, please visit source site