Akademik Veri Yönetim Sistemi
Statistics & Data Science: Concepts, Methods, and Applications, Mükerrem Bahar Başkır,Elmas Burcu Mamak Ekinci,Gonca Yıldırım,Pelin Toktaş, Editör, Nobel Yayınevi, Ankara, ss.331-341, 2025
In recent years, the rapid increase in data generation and information flow has rendered traditional data processing methods insufficient and brought the concept of big data to the forefront. Big data refers to data sets that exceed conventional data structures in terms of volume, velocity, and variety, and are complex to process and analyze. In this context, deep learning techniques have emerged as prominent tools for effectively analyzing big data and transforming it into meaningful information. Deep learning enables the automatic learning of data representations through multilayered artificial neural networks, delivering highly accurate results particularly in fields such as image processing, natural language processing, and predictive analytics. This review study outlines the fundamental dimensions and processing stages of big data, followed by an explanation of the basic structure of deep learning, its primary algorithms, and the advantages it offers in big data environments. Furthermore, the intersection of these two concepts is discussed in terms of application domains and encountered challenges. The aim of the study is to provide researchers and practitioners with a holistic perspective on how big data and deep learning can be effectively utilized together.