… single work offering an overview of Explainable Reinforcement Learning (XRL) methods,
this survey attempts to address this gap. We give a short summary of the problem, a definition …

… , and the development of deep learning and enhanced learning based on big data continued.
… means of machine learning, it can predict both risks and the direction of the stock market. …

… learning and imbalance learning, which limits the improvement of medical image segmentation
based … present a novel survey on medical image segmentation using deep learning. In …

… literature review of current studies on deep learning-based retail product recognition. Our
detailed survey presents challenges, techniques, and open datasets for deep learning-based …

… proposed a computational model based on ML and … study the bioinformatics of pathogen
genomes. Therefore, potential vaccine candidates are identified. The dataset used in this study …

… model presented in this study provides satisfactory detection performance. Some methods
detect abnormal movements of individuals by combining deep learning with patterns, such as …

… of the stock market and cryptocurrencies based on the market … surveys frequently skip
some of the sentiment analysis … of machine learning, transformer learning, and lexicon-based …

… , business, accounting, finance, marketing, economics, stock market, and law, among others
… , content analysis, and social network techniques. In this study, a state-of-the-art research …

… In this study, we study recent COVID-19 tweets related to sentiment classification works
around the world. However, there are no such existing works in Nepali language to this date. …

… stock market forecasting model.[8] Increased attempts are being made to apply deep learning
to stock market … Similarly, derived from the study of human vision, the attention mechanism …