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Machine Learning for Time Series Forecasting with Python
Learn how to apply the principles of machine learning to time series modeling with this indispensable resource Machine Learning for Time Series Forecasting with Python is an incisive and straightforward examination of one of the most crucial elements of decision-making in finance, marketing, education, and healthcare: time series modeling. Despite the centrality of time series forecasting, few business analysts are familiar with the power or utility of applying machine learning to time series modeling. Author Francesca Lazzeri, a distinguished machine learning scientist and economist, corrects that deficiency by providing readers with comprehensive and approachable explanation and treatment ...
Time Series Forecasting
Learn how to build and operationalize machine learning forecast models for your everyday projects. With this practical book, experienced and novice data scientists, business analysts, and AI developers will learn the steps necessary for building, training, and deploying time series forecasting models for their organizations. Time series data is an invaluable source of information used for future strategy and planning operations in several industries. From finance to education and health care, time series forecasting plays a major role in unlocking business insights with respect to time. During the past few decades, machine learning model-based forecasting has become popular in both the private and the public decision-making process.
Impact of Artificial Intelligence in Business and Society
Belonging to the realm of intelligent technologies, it is increasingly accepted that artificial intelligence (AI) has evolved from being merely a development standpoint in computer science. Indeed, recent reports and academic publications show that we are clearly on the path toward pervasive AI in both business and society. Organizations must adopt AI to maintain a competitive advantage and explore opportunities for unprecedented innovation. This book focuses on understanding the wide range of opportunities as well as the spectrum of challenges AI brings in different business contexts and society at large. The book highlights novel and high-quality research in data science and business analy...
Interpretable Machine Learning
This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.
Extending Power BI with Python and R
Perform more advanced analysis and manipulation of your data beyond what Power BI can do to unlock valuable insights using Python and R Key FeaturesGet the most out of Python and R with Power BI by implementing non-trivial codeLeverage the toolset of Python and R chunks to inject scripts into your Power BI dashboardsImplement new techniques for ingesting, enriching, and visualizing data with Python and R in Power BIBook Description Python and R allow you to extend Power BI capabilities to simplify ingestion and transformation activities, enhance dashboards, and highlight insights. With this book, you'll be able to make your artifacts far more interesting and rich in insights using analytical...
Management System for Strategic Innovation
Strategic innovation dynamically brings about strategic positioning through new products, services and business models, and is a dynamic view of strategy that enables a corporation to maintain its competitive advantage and establish sustainable growth. For these reasons, corporations have to be innovators that can reinforce their existing positions through incremental innovation, while at the same time constantly renewing or destroying existing business through radical innovation. This book presents a holistic theoretical model, The Strategic Innovation System, as a system of capabilities for companies to achieve strategic innovation. As a subsystem of the Strategic Innovation System, this b...
Digital Business Strategy
Digital Business Strategy responds to the need for clarification of the increasing, but fragmented, knowledge of digital business strategy. It systematically presents topical knowledge by reviewing previous research and developing frameworks for the content of digital business strategy and its relationships with relevant factors. In addition, the book analyses issues encountered by individual companies when implementing digital business strategies. The volume identifies key categories of digital business strategy, in particular, strategy scope and direction, competitive advantage, and resource and capability reliance. It then explores relationships with antecedents such as digital experience...
Cyber Security and Business Intelligence
To cope with the competitive worldwide marketplace, organizations rely on business intelligence to an increasing extent. Cyber security is an inevitable practice to protect the entire business sector and its customer. This book presents the significance and application of cyber security for safeguarding organizations, individuals’ personal information, and government. The book provides both practical and managerial implications of cyber security that also supports business intelligence and discusses the latest innovations in cyber security. It offers a roadmap to master degree students and PhD researchers for cyber security analysis in order to minimize the cyber security risk and protect ...
Grassroots Innovation
This book explores the process of grassroots innovation in the context of the Global South. It explains why these bottom-up solutions developed by common people are generated due to a lack of available or affordable technology to meet their needs and how they are included in the mainstream imagination of the economy by studying these innovations in India. It analyses the grassroots innovation process from idea generation to its implementation. Detailing both theoretical and practical dimensions of grassroots innovation, the book provides a holistic understanding of the phenomenon by tracing its history in the pre-independence discourse on development to the present-day policies for instituti...
Nuclear Cardiology, An Issue of Cardiology Clinics, E-Book
In this issue of Cardiology Clinics, guest editors Drs. Sharmila Dorbala and Piotr Slomka bring their considerable expertise to the topic of Nuclear Cardiology. Top experts in the field cover key topics such as advances in single-photon emission computed tomography hardware and software; technical aspects of cardiac PET; novel PET applications and radiotracers of imaging cardiovascular pathophysiology; radionuclide tracers for myocardial perfusion imaging and blood flow quantification; and more. - Contains 16 relevant, practice-oriented topics including artificial intelligence in nuclear cardiology; what is new in risk assessment in nuclear cardiology; radionuclide assessments and imaging for various conditions; low radiation dose myocardial perfusion imaging; myocardial perfusion imaging with calcium score; and more. - Provides in-depth clinical reviews on nuclear cardiology, offering actionable insights for clinical practice. - Presents the latest information on this timely, focused topic under the leadership of experienced editors in the field. Authors synthesize and distill the latest research and practice guidelines to create clinically significant, topic-based reviews.
