Literature Review and Theoretical Review of Natural Language Processing (NLP) Introduction Natural Language Processing (NLP) is a branch of artificial intelligence that focuses on the interaction between computers and human (natural) languages. It involves designing algorithms and models to enabl...
Introduction Deep Learning (DL) is a subset of machine learning that uses neural networks with many layers (deep neural networks) to model complex patterns in data. Over the past decade, deep learning has transformed fields such as computer vision, natural language processing, and speech recognitio
Introduction Machine Learning (ML) is a subfield of artificial intelligence (AI) that focuses on the development of algorithms that enable computers to learn from and make predictions or decisions based on data. Over the past few decades, machine learning has evolved significantly and has become an
Abstract Enhancing Women's Participation in Global Value Chains through Machine Learning: A Framework for Economic Inclusion and Growth The integration of women into global value chains (GVCs) is recognized as a pivotal strategy for fostering economic inclusion and sustainable growth. However, pers
The title of this study, "Enhancing Women's Participation in Global Value Chains through Machine Learning: A Framework for Economic Inclusion and Growth," encapsulates the central focus of our research. By leveraging the capabilities of machine learning, we aim to develop a comprehensiv...
However, despite concerted efforts to promote gender equality and women's empowerment, significant challenges persist in realizing the full potential of women's participation in GVCs. Barriers such as limited access to education and training, gender-based discrimination, and unequal opportunitie
Neural Network: Literature Review: Neural networks can analyze complex, high-dimensional data to uncover patterns and relationships that traditional regression techniques may miss. Studies utilizing neural networks might explore how various factors interact to influence women's participation in GVC
Support Vector Regression (SVR): Literature Review: SVR can be applied to predict labor demand in different sectors of the economy, including those involved in GVCs. Research using SVR might forecast the future demand for skilled labor in manufacturing industries, providing insights into potentia