Revolutionizing Data Science and Analytics for Industry TransformationКНИГИ » ПРОГРАММИНГ
Название: Revolutionizing Data Science and Analytics for Industry Transformation Автор: Paul Devasahayam Manuel, Kalim Uddin Qureshi, Thamilarasi Venkatachalam Издательство: IGI Global Scientific Publishing Год: 2025 Страниц: 406 Язык: английский Формат: pdf (true), epub Размер: 21.7 MB
The fields of Data Science and analytics are always evolving. By understanding and navigating the data-driven revolution, advancements can be made in domains such as healthcare, finance, education, and more. Harnessing the power of data in decision-making and problem-solving across industries, industries may advance their methods of data collection, data visualization, and predictive modeling. As such, it is important to stay abreast of the latest developments, methodologies, and trends in data-driven research. Revolutionizing Data Science and Analytics for Industry Transformation contributes to fostering collaboration, innovation, and excellence in Data Science research. It democratizes access to knowledge and empowers individuals and organizations to thrive in the data-driven era. Covering topics such as outcome prediction, deep reinforcement learning, and Mask Attention BERT Networks, this book is an excellent resource for data scientists, business professionals, policymakers, computer scientists, statisticians, engineers, professionals, researchers, scholars, academicians, and more.
Typically, data professionals create visualizations to display the data to a specific audience or for their own purpose. They make use of the selected programming languages' and tools' visualization libraries. Researchers and data scientists often employ proprietary technologies for complex statistical analysis or freely available programming languages like Python. Visualizations help academics and data scientists comprehend data sets better and see developments or patterns that they might have missed otherwise. Plotting libraries such as Matplotlib, Seaborn, and numerous more are available in Python and offer a variety of capabilities that allow users to create visually appealing, personalized, and educational graphs that show data in the most direct and efficient manner possible. The Python libraries utilized for visualization of data include Matplotlib, Seaborn and so on. They come with built-in structures for graphing more types of data. Although graphs can be embedded into programs using Matplotlib, statistical graphs are the main use case for Seaborn. Data visualisation is the process of visually expressing our data to identify patterns and relationships. There are several Python modules available for data visualisation, including Matplotlib, Seaborn, Plotly, and others.
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Revolutionizing Data Science and Analytics for Industry Transformation 
