Seema Rawat – författare

Data Analytics using Machine Learning Techniques on Cloud Platforms examines how machine learning (ML) and cloud computing combine to drive data-driven decision-making across industries. Covering ML techniques, loud-based analytics tools and security concerns, this book provides theoretical foundations and real-world applications in fields like healthcare, logistics and e-commerce. It also addresses security challenges, privacy concerns and compliance frameworks, ensuring a comprehensive understanding of cloud-based analytics. This book: Covers supervised and unsupervised learning, including regression, clustering, classification and neural networksDiscusses Hadoop, Spark, Tableau, Power BI and Splunk for analytics and visualizationExamines how cloud computing enhances scalability, efficiency and automation in data analyticsShowcases ML-driven solutions in e-commerce, supply chain logistics, healthcare and educationThis book is an essential resource for students, researchers and professionals who seek to understand and apply ML-driven cloud analytics in real-world scenarios.

Designer foods can be defined as food items which are designed to deliver health benefits beyond their nutritional value. These can be considered as functional or fortified foods and usually contain additional components or qualities that can be tailored for the treatment and prevention of various diseases. Designer foods are also consumed for their enhanced flavor and can be utilized to combat food scarcity. There is also a global concern regarding the health hazards of chemicals used in modern foods as additives, antioxidants, colorants, flavors and preservatives, some of which have potential harmful effects. Rising health concerns amongst consumers have led to an increasing demand for food items supplemented with natural and healthy ingredients. In addition to their health benefits, designer foods which are either totally microbially-derived or contain ingredients of microbial origin can also provide a solution to the harmful effects of chemicals. The advent of microbial-biotechnology and fermentation technology has expanded the production of designer foods using microorganisms, including the replacement of animal proteins with vegan proteins and colorants derived from microbial pigments.Microbial Based Designer Foods discusses the development, preparation, economics and future prospects of designer foods produced using microorganisms and utilizing ingredients of microbial origin. The text also focuses on the global regulatory status of these designer foods, offering deep insight to the researchers, food technologists and students interested in the development of designer foods which act as a solution to food scarcity and deliver health benefits to consumers. The main topics covered are:Biotechnological and microbiological processes for improvement of food production including suitable research examplesCharacterization and improvement of designer foods for health promotion and disease preventionDevelopment and standardization strategies for designer foods and ingredients produced through biotechnological interventionsEconomic values, global regulatory status, prospects and future of designer foods produced using micro-biotechnological methodsFor researchers and food technologists seeking a comprehensive single source for up-to-date information on microbial based designer foods, this text presents the full picture on this increasingly popular and important food type.

This book uncovers stakes and possibilities offered by Computational Intelligence and Predictive Analytics to Medical Science. The main focus is on data technologies,classification, analysis and mining, information retrieval, and in the algorithms needed to elaborate the informations. A section with use cases and applications follows the two main parts of the book, respectively dedicated to the foundations and techniques of the discipline.

This book emphasizes the applications of advances in data processing methods for Artificial Intelligence in today's fast-changing world, as well as to serve society through research, innovation, and development in this field. This book is applicable to a wide range of data that contribute to data science concerns and can be used to promote research in this high-potential new field. People's perceptions of the world and how they conduct their lives have changed dramatically as a result of technological advancements. The world has been gripped by technology, and the advances that are being made every day are undeniably transforming the planet. In the domains of Big Data, engineering, and data science, this cutting-edge technology is ready to support us.Artificial intelligence (AI) is a current research topic because it can be applied to a wide range of applications and disciplines to solve complicated problems and find optimal solutions. In research, medicine, technology, and the social sciences, the benefits of AI have already been proven. Data science, also known as pattern analytics and mining, is a technique for extracting useful and relevant information from databases, enabling better decision-making and strategy formulation in a range of fields. As a result of the exponential growth of data in recent years, the combined notions of big data and AI have given rise to many study areas, such as scale-up behaviour from classical algorithms. Furthermore, combining numerous AI technologies from other areas (such as vision, security, control, and biology) in order to build efficient and durable systems that interact in the real world is a new problem. Despite recent improvements in fundamental AI technologies, the integration of these skills into larger, trustworthy, transparent, and maintainable systems is still in its development. Both conceptually and practically, there are a number of unanswered issues.