Research and development in artificial intelligence and its associated domains and subfields, such as machine learning, deep learning, and natural language processing, have undergone tremendous growth over the past several years. This increase may be attributed to the rise in popularity of these areas of study. As a result of the availability of a vast diversity of applications and the declining cost of computer systems, researchers have discovered a renewed sensation of excitement in the job that they do. In the modern world, I believe it is fair to state that artificial intelligence and the subfields that fall under its umbrella have been having a favourable impact on a wide variety of business sectors. Machine learning and deep learning not only make companies more efficient, but they have also had a substantial influence on various subfields of artificial intelligence, such as computer vision and natural language processing. Both of these types of learning increase the efficiency of enterprises. Learning techniques have played a very essential part in ensuring that correct analysis is carried out in the field of natural language processing, which refers to the capacity of computers to comprehend human languages. This is a challenging endeavour. In this study, we focus on the significant part that learning strategies play in enhancing the productive capacity of natural language processing.
Machine Learning, Deep Learning, Natural Language Processing, Artificial Intelligence.
IRE Journals:
Adheer Arun Goyal
"The Role of Machine Learning in Natural Language Processing and Computer Vision" Iconic Research And Engineering Journals Volume 6 Issue 11 2023 Page 185-195
IEEE:
Adheer Arun Goyal
"The Role of Machine Learning in Natural Language Processing and Computer Vision" Iconic Research And Engineering Journals, 6(11)