This book introduces the field of data science in a practical and accessible manner, using a hands-on approach that assumes no prior knowledge of the subject. The foundational ideas and techniques of data science are provided independently from technology, allowing students to easily develop a firm understanding of the subject without a strong technical background, as well as being presented with material that will have continual relevance even after tools and technologies change. Using popular data science tools such as Python and R, the book offers many examples of real-life applications, with practice ranging from small to big data. A suite of online material for both instructors and students provides a strong supplement to the book, including datasets, chapter slides, solutions, sample exams and curriculum suggestions. This entry-level textbook is ideally suited to readers from a range of disciplines wishing to build a practical, working knowledge of data science.
Since user study design has been widely applied in search interactions and information retrieval (IR) systems evaluation studies, a deep reflection and meta-evaluation of interactive IR (IIR) user studies is critical for sharpening the instruments of IIR research and improving the reliability and validity of the conclusions drawn from IIR user studies. To this end, we developed a faceted framework for supporting user study design, reporting, and evaluation based on a systematic review of the state-of-the-art IIR research papers recently published in several top IR venues (n=462). Within the framework, we identify three major types of research focuses, extract and summarize facet values from specific cases, and highlight the under-reported user study components which may significantly affect the results of research. Then, we employ the faceted framework in evaluating a series of IIR user studies against their respective research questions and explain the roles and impacts of the underlying connections and "collaborations" among different facet values. Through bridging diverse combinations of facet values with the study design decisions made for addressing research problems, the faceted framework can shed light on IIR user study design, reporting, and evaluation practices and help students and young researchers design and assess their own studies.
This volume summarizes the author’s work on social information seeking (SIS), and at the same time serves as an introduction to the topic. Sometimes also referred to as social search or social information retrieval, this is a relatively new area of study concerned with the seeking and acquiring of information from social spaces on the Internet. It involves studying situations, motivations, and methods involved in seeking and sharing of information in participatory online social sites, such as Yahoo! Answers, WikiAnswers, and Twitter, as well as building systems for supporting such activities. The first part of the book introduces various foundational concepts, including information seeking, social media, and social networking. As such it provides the necessary basis to then discuss how those aspects could intertwine in different ways to create methods, tools, and opportunities for supporting and leveraging SIS. Next, Part II discusses the social dimension and primarily examines the online question-answering activity. Part III then emphasizes the collaborative aspect of information seeking, and examines what happens when social and collaborative dimensions are considered together. Lastly, Part IV provides a synthesis by consolidating methods, systems, and evaluation techniques related to social and collaborative information seeking. The book is completed by a list of challenges and opportunities for both theoretical and practical SIS work. The book is intended mainly for researchers and graduate students looking for an introduction to this new field, as well as developers and system designers interested in building interactive information retrieval systems or social/community-driven interfaces.
While great strides have been made in the field of search and recommendation, there are still challenges and opportunities to address information access issues that involve solving tasks and accomplishing goals for a wide variety of users. Specifically, we lack intelligent systems that can detect not only the request an individual is making (what), but also understand and utilize the intention (why) and strategies (how) while providing information and enabling task completion. Many scholars in the fields of information retrieval, recommender systems, productivity (especially in task management and time management), and artificial intelligence have recognized the importance of extracting and understanding people's tasks and the intentions behind performing those tasks in order to serve them better. However, we are still struggling to support them in task completion, e.g., in search and assistance, and it has been challenging to move beyond single-query or single-turn interactions. The proliferation of intelligent agents has unlocked new modalities for interacting with information, but these agents will need to be able to work understanding current and future contexts and assist users at task level. This book will focus on task intelligence in the context of search and recommendation. Chapter 1 introduces readers to the issues of detecting, understanding, and using task and task-related information in an information episode (with or without active searching). This is followed by presenting several prominent ideas and frameworks about how tasks are conceptualized and represented in Chapter 2. In Chapter 3, the narrative moves to showing how task type relates to user behaviors and search intentions. A task can be explicitly expressed in some cases, such as in a to-do application, but often it is unexpressed. Chapter 4 covers these two scenarios with several related works and case studies. Chapter 5 shows how task knowledge and task models can contribute to addressing emerging retrieval and recommendation problems. Chapter 6 covers evaluation methodologies and metrics for task-based systems, with relevant case studies to demonstrate their uses. Finally, the book concludes in Chapter 7, with ideas for future directions in this important research area.
Today’s complex, information-intensive problems often require people to work together. Mostly these tasks go far beyond simply searching together; they include information lookup, sharing, synthesis, and decision-making. In addition, they all have an end-goal that is mutually beneficial to all parties involved. Such “collaborative information seeking” (CIS) projects typically last several sessions and the participants all share an intention to contribute and benefit. Not surprisingly, these processes are highly interactive. Shah focuses on two individually well-understood notions: collaboration and information seeking, with the goal of bringing them together to show how it is a natural tendency for humans to work together on complex tasks. The first part of his book introduces the general notions of collaboration and information seeking, as well as related concepts, terminology, and frameworks; and thus provides the reader with a comprehensive treatment of the concepts underlying CIS. The second part of the book details CIS as a standalone domain. A series of frameworks, theories, and models are introduced to provide a conceptual basis for CIS. The final part describes several systems and applications of CIS, along with their broader implications on other fields such as computer-supported cooperative work (CSCW) and human-computer interaction (HCI). With this first comprehensive overview of an exciting new research field, Shah delivers to graduate students and researchers in academia and industry an encompassing description of the technologies involved, state-of-the-art results, and open challenges as well as research opportunities.
The best physician-specific general financial book published in 2021." —James M. Dahle, MD, author of The White Coat Investor A step-by-step guidebook for doctors and other medical professionals about growing and preserving wealth, Financial Freedom Rx: The Physician’s Guide to Achieving Financial Independence gives physicians all the tools necessary to manage their own finances and includes a foreword by Mel Lindauer, co-author of The Bogleheads' Guide to Investing. Medical professionals, especially doctors, spend many years in training as they accumulate debt and delay their earnings. This book presents a time-tested formula that students and established professionals can follow at any stage during their careers to achieve fiscal peace of mind. Students will learn how to budget and adopt disciplined financial practices. Residents and other trainees will learn how to defend against calamity with various insurances and how to manage debt. Junior professionals will acquire the skills needed to invest and grow their portfolios, while senior professionals will better understand the essentials of estate planning and retirement. Drs. Chirag P. Shah and Jayanth Sridhar wrote this inspiring text to guide physicians where to put their next dollar. This is particularly important during the financial uncertainties brought on by COVID-19 and insurance cuts. Financial Freedom Rx sets forth principles that will pilot medical professionals toward financial independence. Chapters include useful advice on topics such as: Financial planning Investing and asset allocation Jobs and contracts Taxes and insurance Student loans and debt Retirement savings and distributions Financial Freedom Rx: The Physician’s Guide to Achieving Financial Independence serves as a timeless blueprint for financial planning that medical professionals will follow throughout their careers, and as a reference that readers will revisit again and again as they progress through the various stages of life.
Financial Freedom Rx is a book directed toward physicians and their unique financial situation. This book provides specific guidance on where you should put your next dollar depending on where you are financially in life. The goal is to help readers achieve financial independence and peace of mind"--
Now in full color and completely updated, the Fifth Edition of this best-selling manual is a reliable quick-reference guide for all clinicians who treat eye disorders. Every disorder encountered in the office, emergency room, or hospital is covered in concise outline format: symptoms, signs, work-up, treatment, and follow-up. Also included are chapters on differential diagnosis of ocular symptoms and signs, a section on current imaging modalities in ophthalmology, and a Pharmacopoeia. This edition features over 200 full-color photographs and includes the newest drugs, procedures, and treatment protocols. New topics covered include iridodialysis/cyclodialysis, shaken baby syndrome, crystalline keratopathy, refractive surgery complications, aberrant regeneration of the third nerve, venous stasis retinopathy, choroidal effusion/detachment, and common laser procedures. New appendices cover intravitreal injections and antibiotics, anterior chamber paracentesis, laser peripheral iridotomy, and YAG capsulotomy
This book introduces the field of data science in a practical and accessible manner, using a hands-on approach that assumes no prior knowledge of the subject. The foundational ideas and techniques of data science are provided independently from technology, allowing students to easily develop a firm understanding of the subject without a strong technical background, as well as being presented with material that will have continual relevance even after tools and technologies change. Using popular data science tools such as Python and R, the book offers many examples of real-life applications, with practice ranging from small to big data. A suite of online material for both instructors and students provides a strong supplement to the book, including datasets, chapter slides, solutions, sample exams and curriculum suggestions. This entry-level textbook is ideally suited to readers from a range of disciplines wishing to build a practical, working knowledge of data science.
While great strides have been made in the field of search and recommendation, there are still challenges and opportunities to address information access issues that involve solving tasks and accomplishing goals for a wide variety of users. Specifically, we lack intelligent systems that can detect not only the request an individual is making (what), but also understand and utilize the intention (why) and strategies (how) while providing information and enabling task completion. Many scholars in the fields of information retrieval, recommender systems, productivity (especially in task management and time management), and artificial intelligence have recognized the importance of extracting and understanding people's tasks and the intentions behind performing those tasks in order to serve them better. However, we are still struggling to support them in task completion, e.g., in search and assistance, and it has been challenging to move beyond single-query or single-turn interactions. The proliferation of intelligent agents has unlocked new modalities for interacting with information, but these agents will need to be able to work understanding current and future contexts and assist users at task level. This book will focus on task intelligence in the context of search and recommendation. Chapter 1 introduces readers to the issues of detecting, understanding, and using task and task-related information in an information episode (with or without active searching). This is followed by presenting several prominent ideas and frameworks about how tasks are conceptualized and represented in Chapter 2. In Chapter 3, the narrative moves to showing how task type relates to user behaviors and search intentions. A task can be explicitly expressed in some cases, such as in a to-do application, but often it is unexpressed. Chapter 4 covers these two scenarios with several related works and case studies. Chapter 5 shows how task knowledge and task models can contribute to addressing emerging retrieval and recommendation problems. Chapter 6 covers evaluation methodologies and metrics for task-based systems, with relevant case studies to demonstrate their uses. Finally, the book concludes in Chapter 7, with ideas for future directions in this important research area.
Packed with real-world examples, industry insights and practical activities, this textbook is designed to teach machine learning in a way that is easy to understand and apply. It assumes only a basic knowledge of technology, making it an ideal resource for students and professionals, including those who are new to computer science. All the necessary topics are covered, including supervised and unsupervised learning, neural networks, reinforcement learning, cloud-based services, and the ethical issues still posing problems within the industry. While Python is used as the primary language, many exercises will also have the solutions provided in R for greater versatility. A suite of online resources is available to support teaching across a range of different courses, including example syllabi, a solutions manual, and lecture slides. Datasets and code are also available online for students, giving them everything they need to practice the examples and problems in the book.
The best physician-specific general financial book published in 2021." —James M. Dahle, MD, author of The White Coat Investor A step-by-step guidebook for doctors and other medical professionals about growing and preserving wealth, Financial Freedom Rx: The Physician’s Guide to Achieving Financial Independence gives physicians all the tools necessary to manage their own finances and includes a foreword by Mel Lindauer, co-author of The Bogleheads' Guide to Investing. Medical professionals, especially doctors, spend many years in training as they accumulate debt and delay their earnings. This book presents a time-tested formula that students and established professionals can follow at any stage during their careers to achieve fiscal peace of mind. Students will learn how to budget and adopt disciplined financial practices. Residents and other trainees will learn how to defend against calamity with various insurances and how to manage debt. Junior professionals will acquire the skills needed to invest and grow their portfolios, while senior professionals will better understand the essentials of estate planning and retirement. Drs. Chirag P. Shah and Jayanth Sridhar wrote this inspiring text to guide physicians where to put their next dollar. This is particularly important during the financial uncertainties brought on by COVID-19 and insurance cuts. Financial Freedom Rx sets forth principles that will pilot medical professionals toward financial independence. Chapters include useful advice on topics such as: Financial planning Investing and asset allocation Jobs and contracts Taxes and insurance Student loans and debt Retirement savings and distributions Financial Freedom Rx: The Physician’s Guide to Achieving Financial Independence serves as a timeless blueprint for financial planning that medical professionals will follow throughout their careers, and as a reference that readers will revisit again and again as they progress through the various stages of life.
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