Machine Learning and Data Science: Fundamentals and Applications

Machine learning and data science are active topics with a wide scope, driving research and practical transformation in various domains. They encompass innovative algorithms for artificial intelligence, data analytics, pattern recognition, natural language understanding, and big data manipulation. These algorithms address challenges in data capture, creation, storage, retrieval, sharing, analysis, optimization, and visualization, leading to better decision-making, collaboration, and value creation.

Format: Hardback
Length: 272 pages
Publication date: 08 August 2022
Publisher: John Wiley & Sons Inc

Machine learning (ML) and data science (DS) are dynamic and rapidly evolving fields with a vast scope, encompassing both theoretical and practical aspects. They have emerged as significant scientific paradigms, driving research advancements across disciplines such as statistics, computing science, and intelligence science. At the same time, their applications have brought about transformative changes in various domains, including science, engineering, public sector, business, social science, and lifestyle. These fields face significant challenges that often require innovative machine learning and data science algorithms to address.

These algorithms encompass a wide range of areas, including artificial intelligence, data analytics, machine learning, pattern recognition, natural language understanding, and big data manipulation. They also address emerging scientific challenges related to data capture, creation, storage, retrieval, sharing, analysis, optimization, and visualization. Furthermore, they strive to integrate and analyze heterogeneous and interdependent complex resources to enhance decision-making, collaboration, and value creation.

The field of ML and DS has witnessed remarkable growth and development in recent years, driven by advancements in computing power, data availability, and analytical techniques. This has led to the development of new algorithms, models, and frameworks that have the potential to revolutionize industries and improve human lives. However, there are also ongoing challenges and ethical considerations that need to be addressed to ensure the responsible and ethical use of ML and DS technologies.

In conclusion, ML and DS are powerful tools that have the potential to transform various industries and improve our understanding of the world. They require interdisciplinary collaboration, innovative thinking, and ethical considerations to realize their full potential. As the field continues to evolve, it will be important to stay updated with the latest developments, address challenges, and promote the responsible and ethical use of these technologies.
Machine learning (ML) and data science (DS) are dynamic and rapidly evolving fields with a vast scope, encompassing both theoretical and practical aspects. They have emerged as significant scientific paradigms, driving research advancements across disciplines such as statistics, computing science, and intelligence science. At the same time, their applications have brought about transformative changes in various domains, including science, engineering, public sector, business, social science, and lifestyle. These fields face significant challenges that often require innovative machine learning and data science algorithms to address.

These algorithms encompass a wide range of areas, including artificial intelligence, data analytics, machine learning, pattern recognition, natural language understanding, and big data manipulation. They also address emerging scientific challenges related to data capture, creation, storage, retrieval, sharing, analysis, optimization, and visualization. Furthermore, they strive to integrate and analyze heterogeneous and interdependent complex resources to enhance decision-making, collaboration, and value creation.

The field of ML and DS has witnessed remarkable growth and development in recent years, driven by advancements in computing power, data availability, and analytical techniques. This has led to the development of new algorithms, models, and frameworks that have the potential to revolutionize industries and improve human lives. However, there are also ongoing challenges and ethical considerations that need to be addressed to ensure the responsible and ethical use of ML and DS technologies.

In conclusion, ML and DS are powerful tools that have the potential to transform various industries and improve our understanding of the world. They require interdisciplinary collaboration, innovative thinking, and ethical considerations to realize their full potential. As the field continues to evolve, it will be important to stay updated with the latest developments, address challenges, and promote the responsible and ethical use of these technologies.

Weight: 453g
Dimension: 10 x 10 x 10 (mm)
ISBN-13: 9781119775614