An Inclusive Review on Recent Trends, Advances and Emerging Areas within Deep Learning Community

Deep learning, an innovative discipline, has effectively tackled previously considered impossible obstacles, particularly in the automated identification of data patterns, frequently surpassing human precision. It surpasses conventional machine learning, enticing specialists who are struggling with the immense amount of data. With the increase in public awareness, there is also a corresponding increase in the desire to utilize deep learning. Nevertheless, manoeuvring over this complex terrain might be intimidating. This overview provides a comprehensive exploration of fundamental multilayer artificial neural networks in the field of deep learning. The study examines the use of multi-agent techniques to optimize architecture automatically. The review examines the increasing significance of system uptime and provides analysis on the utilization of neural networks for identifying and resolving faults. Furthermore, it examines innovative uses in anomaly detection, “financial time-series forecasting, predictive analytics, medical image analysis, and power systems research.”