Enabling AI Applications in Data Science - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Enabling AI Applications in Data Science write by Aboul-Ella Hassanien. This book was released on 2020-09-23. Enabling AI Applications in Data Science available in PDF, EPUB and Kindle. This book provides a detailed overview of the latest developments and applications in the field of artificial intelligence and data science. AI applications have achieved great accuracy and performance with the help of developments in data processing and storage. It has also gained strength through the amount and quality of data which is the main nucleus of data science. This book aims to provide the latest research findings in the field of artificial intelligence with data science.
Artificial Intelligence, Data Science and Applications
Artificial Intelligence, Data Science and Applications - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Artificial Intelligence, Data Science and Applications write by Yousef Farhaoui. This book was released on . Artificial Intelligence, Data Science and Applications available in PDF, EPUB and Kindle.
Applying Data Science
Applying Data Science - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Applying Data Science write by Arthur K. Kordon. This book was released on 2021-09-14. Applying Data Science available in PDF, EPUB and Kindle. This book offers practical guidelines on creating value from the application of data science based on selected artificial intelligence methods. In Part I, the author introduces a problem-driven approach to implementing AI-based data science and offers practical explanations of key technologies: machine learning, deep learning, decision trees and random forests, evolutionary computation, swarm intelligence, and intelligent agents. In Part II, he describes the main steps in creating AI-based data science solutions for business problems, including problem knowledge acquisition, data preparation, data analysis, model development, and model deployment lifecycle. Finally, in Part III the author illustrates the power of AI-based data science with successful applications in manufacturing and business. He also shows how to introduce this technology in a business setting and guides the reader on how to build the appropriate infrastructure and develop the required skillsets. The book is ideal for data scientists who will implement the proposed methodology and techniques in their projects. It is also intended to help business leaders and entrepreneurs who want to create competitive advantage by using AI-based data science, as well as academics and students looking for an industrial view of this discipline.
Machine Learning and Data Science
Machine Learning and Data Science - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Machine Learning and Data Science write by Prateek Agrawal. This book was released on 2022-07-25. Machine Learning and Data Science available in PDF, EPUB and Kindle. MACHINE LEARNING AND DATA SCIENCE Written and edited by a team of experts in the field, this collection of papers reflects the most up-to-date and comprehensive current state of machine learning and data science for industry, government, and academia. Machine learning (ML) and data science (DS) are very active topics with an extensive scope, both in terms of theory and applications. They have been established as an important emergent scientific field and paradigm driving research evolution in such disciplines as statistics, computing science and intelligence science, and practical transformation in such domains as science, engineering, the public sector, business, social science, and lifestyle. Simultaneously, their applications provide important challenges that can often be addressed only with innovative machine learning and data science algorithms. These algorithms encompass the larger areas of artificial intelligence, data analytics, machine learning, pattern recognition, natural language understanding, and big data manipulation. They also tackle related new scientific challenges, ranging from data capture, creation, storage, retrieval, sharing, analysis, optimization, and visualization, to integrative analysis across heterogeneous and interdependent complex resources for better decision-making, collaboration, and, ultimately, value creation.
Data Science and Its Applications
Data Science and Its Applications - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Data Science and Its Applications write by Aakanksha Sharaff. This book was released on 2021-08-18. Data Science and Its Applications available in PDF, EPUB and Kindle. The term "data" being mostly used, experimented, analyzed, and researched, "Data Science and its Applications" finds relevance in all domains of research studies including science, engineering, technology, management, mathematics, and many more in wide range of applications such as sentiment analysis, social medial analytics, signal processing, gene analysis, market analysis, healthcare, bioinformatics etc. The book on Data Science and its applications discusses about data science overview, scientific methods, data processing, extraction of meaningful information from data, and insight for developing the concept from different domains, highlighting mathematical and statistical models, operations research, computer programming, machine learning, data visualization, pattern recognition and others. The book also highlights data science implementation and evaluation of performance in several emerging applications such as information retrieval, cognitive science, healthcare, and computer vision. The data analysis covers the role of data science depicting different types of data such as text, image, biomedical signal etc. useful for a wide range of real time applications. The salient features of the book are: Overview, Challenges and Opportunities in Data Science and Real Time Applications Addressing Big Data Issues Useful Machine Learning Methods Disease Detection and Healthcare Applications utilizing Data Science Concepts and Deep Learning Applications in Stock Market, Education, Behavior Analysis, Image Captioning, Gene Analysis and Scene Text Analysis Data Optimization Due to multidisciplinary applications of data science concepts, the book is intended for wide range of readers that include Data Scientists, Big Data Analysists, Research Scholars engaged in Data Science and Machine Learning applications.
