Feature Engineering For Time Series Forecasting Create Lag, Window And Seasonal Features, Perform Imputation And Encoding, Extract Datetime Variables, Remove Outliers.

This Briefs Series book illustrates in depth a concept of healthcare management engineering and its domain for hospital and clinic operations. Predictive and analytic decision-making power of management engineering methodology is systematically compared to traditional management reasoning by applying both side by side to analyze 26 concrete operational management problems adapted from hospital and clinic practice. The problem types include: clinic, bed and operating rooms capacity; patient flow; staffing and scheduling; resource allocation and optimization; forecasting of patient volumes and seasonal variability; business intelligence and data mining; and game theory application for allocating cost savings between cooperating providers.

This textbook introduces readers to the theoretical aspects of machine learning (ML) algorithms, starting from simple neuron basics, through complex neural networks, including generative adversarial neural networks and graph convolution networks. Most importantly, this book helps readers to understand the concepts of ML algorithms and enables them to develop the skills necessary to choose an apt ML algorithm for a problem they wish to solve. In addition, this book includes numerous case studies, ranging from simple time-series forecasting to object recognition and recommender systems using massive databases. Lastly, this book also provides practical implementation examples and assignments for the readers to practice and improve their programming capabilities for the ML applications.

This edited book support Sustainable Development Goal 2 (SDG 2): Zero Hunger. This book summarizes the contribution of genetic engineering for sustainable crop improvement toward global food and health security, climate resilience and economic growth. The book acts as a compendium of research reports on recent developments in the arena of cisgenics or transgenics or genome editing of crop plants for tolerance to biotic or abiotic stresses, introgression of value-added traits, molecular pharming etc. Sustainable crop productivity, yield and nutrition are the major constrain for food and nutritional security for the human population especially, in developing countries where arable land per capita is shrinking while the human population is steadily increasing. Zero hunger and achieving food security is the top priority of the United Nations development goals. This book explains various methods of genetic transformation such as transgenic, cisgenic, and genome editing for crop improvement. It also encompasses the advantages of genetic engineering in plants and their scope for sustainable crop improvement. The importance, limitations, challenges, GM biosafety regulations, recent advancements and future prospects of GM crops are covered in various chapters. This book is of interest to teachers, researchers, plant tissue culturists, GM crop experts, research scholars, academicians, plant breeders, policymakers etc. Also, the book serves as additional reading material for undergraduate and graduate students of agriculture, forestry, ecology, soil science, and environmental sciences. National and international agricultural scientists and policymakers will also find this to be a useful read.

This book takes a fresh look at methodologies used in developing crop plants, discusses genome editing, and interrogates the regulatory approaches that different countries are proposing to use to regulate genetically modified (GM) vs genome-edited crop plants. The book focuses on root and tuber crops, ginger, and industrial/oil seed crops.

Learn imputation, variable encoding, discretization, feature extraction, how to work with datetime, outliers, and more.