How Natural Language Processing has evolved in a few short years with regard to machine learning

I began studying machine learning in 2020 because I wanted to develop a new skill set that I can use professionally. I went onto the Kaggle data science website because Ken Jee, data scientist, suggested that individuals looking to learn data science should go onto that site. I also took courses and watched videos on the various subjects in data science, endeavouring to learn as much as I could about the subject. I started out entering competitions in order to learn data science and to also perfect my skill in machine learning.

One such competition that I entered was Kaggle’s Disaster tweet competition, which concerns making predictions on whether a tweet refers to a disaster or not. As I have tried a variety of techniques to improve the accuracy of the predictions I make on the competition’s associated dataset, I have found that this competition serves as a good benchmark for the progression of natural language processing in data science. In the three short years that I have been working with natural language processing, I have seen the technology in this genre of data science advance significantly. I personally have endeavoured to make predictions on text using the following libraries that have different techniques associated with them:-