Deep Learning Applications in Data Science: Investigating applications of deep learning techniques such as neural networks and convolutional networks in data science tasks

Abstract

Deep learning has revolutionized the field of data science by providing powerful tools to extract valuable insights from complex data. This paper explores the wide-ranging applications of deep learning techniques, such as neural networks and convolutional networks, in various data science tasks. We examine how these techniques are used to tackle challenges in data preprocessing, feature extraction, and model training. Furthermore, we investigate the role of deep learning in predictive analytics, anomaly detection, and natural language processing. Through a comprehensive review of recent literature, we highlight the effectiveness of deep learning in handling large datasets and capturing intricate patterns that are often difficult to detect with traditional machine learning methods. Our analysis reveals the significant impact of deep learning on advancing data science and offers insights into future research directions in this rapidly evolving field.