دانلود کتاب علم داده در کاربردهای اجتماعی

Data science is an amalgamation of various disciplines of research including the method ranging from empirical methods to current trends of data observation along with the application of rigorous skepticism about observations in data, resulting in interprets that involve formulating hypotheses and deducing inductions. These princi-ples of data science have been distinguished in the form of a series of steps applicable to various enterprises. The processes, algorithms, and systems to extract knowledge and insights from a huge amount of structural and unstructured data produced by these enterprises have made data science the need of the hour. The aim is to use the data as raw inputs and generate valuable data products that can be used by enterprises for their business benefits. Data science in societal applications has been established as a new horizon of the scientific field with the silver lining of research evolution in societal applications using renovations in the existing domains of statis-tics, computing science, and intelligence science. The application of advancements in these legacy research domains and its practical transformation in engineering, public sector enterprises, social science, and lifestyle spheres is the way forward. This adds to the ever-increasing importance of data science, both big data and small data, which when analyzed scientifically bring with them a wealth of opportunities that combine the new trends to extract, transport, pool, refine, store, analyze, and visualize data which are needed to unleash their power. This also simultaneously can be incorporated into tool-integrated development environments and workflows that are ready to be used by people in general.
To have a successful career in data science emphasizing its societal applications for the benefit of the public at large is a real challenge. The desired knowledge base includes complex topics from statistics, computer science, and mathematics. In addition to that, domain-specific knowledge becomes essential for user-friendly application developments. The real-time applications of data science are added chal-lenge that requires to be mitigated. Thus, there is a need for conjugation of data science with various real-life applications of computing and implementations. The proposed book intends to provide a range of current trends in the theoretical and practical applications of data science that are being developed and implemented by researchers, academicians, and industries.