Book picks similar to
Machine Learning: A Bayesian and Optimization Perspective by Sergios Theodoridis


machine-learning
data-science
computerscience_m<br/>achinelearning
work-related

Data Science with R


Garrett Grolemund - 2015
    

Fuzzy Thinking: The New Science of Fuzzy Logic


Bart Kosko - 1993
    An authoritative introduction to "fuzzy logic" brings readers up to speed on the "smart" products and computers that will change all of our lives in the future.

Python Crash Course: A Hands-On, Project-Based Introduction to Programming


Eric Matthes - 2015
    You'll also learn how to make your programs interactive and how to test your code safely before adding it to a project. In the second half of the book, you'll put your new knowledge into practice with three substantial projects: a Space Invaders-inspired arcade game, data visualizations with Python's super-handy libraries, and a simple web app you can deploy online.As you work through Python Crash Course, you'll learn how to: Use powerful Python libraries and tools, including matplotlib, NumPy, and PygalMake 2D games that respond to keypresses and mouse clicks, and that grow more difficult as the game progressesWork with data to generate interactive visualizationsCreate and customize simple web apps and deploy them safely onlineDeal with mistakes and errors so you can solve your own programming problemsIf you've been thinking seriously about digging into programming, Python Crash Course will get you up to speed and have you writing real programs fast. Why wait any longer? Start your engines and code!

Ethical Leadership and Decision Making in Education: Applying Theoretical Perspectives to Complex Dilemmas, Third Edition


Joan Poliner Shapiro - 2000
    Ethical Leadership and Decision Making in Education: Applying Theoretical Perspectives to Complex Dilemmas, Second Edition: *demonstrates the application of different ethical paradigms (the ethics of justice, care, critique, and the profession) through discussion and analysis of real-life moral dilemmas that educational leaders face in their schools and communities;*addresses some of the practical, pedagogical, and curricular issues related to the teaching of ethics for educational leaders;*emphasizes the importance of ethics instruction from a variety of theoretical approaches; and*provides a process that instructors might follow to develop their own ethics unit or course.Part I provides an overview of why ethics is so important, especially for today's educational leaders, and presents a multiparadigm approach essential to practitioners as they grapple with ethical dilemmas. Part II deals with the dilemmas themselves. It includes a brief introduction to how the cases were constructed, an illustration of how the multiparadigm approach may be applied to a real dilemma, and ethical dilemmas written by graduate students that represent the kinds of dilemmas faced by practicing administrators in urban, suburban, and rural settings in an era full of complexities and contradictions. Part III focuses on pedagogy and provides teaching notes for the instructor. The authors discuss the importance of self-reflection on the part of both instructors and students, and model how they thought through their own personal and professional ethical codes as well as reflected upon the critical incidents in their lives that shape their teaching and frequently determine what they privileged in class.New in the Second Edition: *A completely new chapter emphasizing religious differences and presenting the contradictions between religion and culture;*A completely new chapter on testing, juxtaposing the paradox of accountability with responsibility;*Several new dilemmas focusing on higher education, recognizing that many educational leadership training programs include students with this focus; and*Changes throughout to update the text, including a discussion of recent scholarship in the field of ethical leadership.Ethical Leadership and Decision Making in Education: Applying Theoretical Perspectives to Complex Dilemmas, Second Edition is easily adaptable for a variety of uses with a wide range of audiences. It is equally valuable as a text for university courses related to the preparation of educational leaders and as a professional reference for aspiring and practicing administrators, teacher leaders, office personnel, and educational policy makers.

The Basics of Digital Forensics: The Primer for Getting Started in Digital Forensics


John Sammons - 2011
    This book teaches you how to conduct examinations by explaining what digital forensics is, the methodologies used, key technical concepts and the tools needed to perform examinations. Details on digital forensics for computers, networks, cell phones, GPS, the cloud, and Internet are discussed. Readers will also learn how to collect evidence, document the scene, and recover deleted data. This is the only resource your students need to get a jump-start into digital forensics investigations.This book is organized into 11 chapters. After an introduction to the basics of digital forensics, the book proceeds with a discussion of key technical concepts. Succeeding chapters cover labs and tools; collecting evidence; Windows system artifacts; anti-forensics; Internet and email; network forensics; and mobile device forensics. The book concludes by outlining challenges and concerns associated with digital forensics. PowerPoint lecture slides are also available.This book will be a valuable resource for entry-level digital forensics professionals as well as those in complimentary fields including law enforcement, legal, and general information security.

Machine, Platform, Crowd: Harnessing Our Digital Future


Andrew McAfee - 2017
    Now they’ve written a guide to help readers make the most of our collective future. Machine | Platform | Crowd outlines the opportunities and challenges inherent in the science fiction technologies that have come to life in recent years, like self-driving cars and 3D printers, online platforms for renting outfits and scheduling workouts, or crowd-sourced medical research and financial instruments.

Computer Systems: A Programmer's Perspective


Randal E. Bryant - 2002
    Often, computer science and computer engineering curricula don't provide students with a concentrated and consistent introduction to the fundamental concepts that underlie all computer systems. Traditional computer organization and logic design courses cover some of this material, but they focus largely on hardware design. They provide students with little or no understanding of how important software components operate, how application programs use systems, or how system attributes affect the performance and correctness of application programs. - A more complete view of systems - Takes a broader view of systems than traditional computer organization books, covering aspects of computer design, operating systems, compilers, and networking, provides students with the understanding of how programs run on real systems. - Systems presented from a programmers perspective - Material is presented in such a way that it has clear benefit to application programmers, students learn how to use this knowledge to improve program performance and reliability. They also become more effective in program debugging, because t

Structure and Interpretation of Computer Programs


Harold Abelson - 1984
    This long-awaited revision contains changes throughout the text. There are new implementations of most of the major programming systems in the book, including the interpreters and compilers, and the authors have incorporated many small changes that reflect their experience teaching the course at MIT since the first edition was published. A new theme has been introduced that emphasizes the central role played by different approaches to dealing with time in computational models: objects with state, concurrent programming, functional programming and lazy evaluation, and nondeterministic programming. There are new example sections on higher-order procedures in graphics and on applications of stream processing in numerical programming, and many new exercises. In addition, all the programs have been reworked to run in any Scheme implementation that adheres to the IEEE standard.

Diffusion of Innovations


Everett M. Rogers - 1982
    It has sold 30,000 copies in each edition and will continue to reach a huge academic audience.In this renowned book, Everett M. Rogers, professor and chair of the Department of Communication & Journalism at the University of New Mexico, explains how new ideas spread via communication channels over time. Such innovations are initially perceived as uncertain and even risky. To overcome this uncertainty, most people seek out others like themselves who have already adopted the new idea. Thus the diffusion process consists of a few individuals who first adopt an innovation, then spread the word among their circle of acquaintances--a process which typically takes months or years. But there are exceptions: use of the Internet in the 1990s, for example, may have spread more rapidly than any other innovation in the history of humankind. Furthermore, the Internet is changing the very nature of diffusion by decreasing the importance of physical distance between people. The fifth edition addresses the spread of the Internet, and how it has transformed the way human beings communicate and adopt new ideas.

Leadership [with Introduction to Leadership]


Peter G. Northouse - 2018
    Northouse's Leadership 8e and Peter G. Northouse's Introduction to Leadership 4e

Introduction to Artificial Intelligence


Philip C. Jackson Jr. - 1974
    Introduction to Artificial Intelligence presents an introduction to the science of reasoning processes in computers, and the research approaches and results of the past two decades. You'll find lucid, easy-to-read coverage of problem-solving methods, representation and models, game playing, automated understanding of natural languages, heuristic search theory, robot systems, heuristic scene analysis and specific artificial-intelligence accomplishments. Related subjects are also included: predicate-calculus theorem proving, machine architecture, psychological simulation, automatic programming, novel software techniques, industrial automation and much more.A supplementary section updates the original book with major research from the decade 1974-1984. Abundant illustrations, diagrams and photographs enhance the text, and challenging practice exercises at the end of each chapter test the student's grasp of each subject.The combination of introductory and advanced material makes Introduction to Artificial Intelligence ideal for both the layman and the student of mathematics and computer science. For anyone interested in the nature of thought, it will inspire visions of what computer technology might produce tomorrow.

Real-Time Big Data Analytics: Emerging Architecture


Mike Barlow - 2013
    The data world was revolutionized a few years ago when Hadoop and other tools made it possible to getthe results from queries in minutes. But the revolution continues. Analysts now demand sub-second, near real-time query results. Fortunately, we have the tools to deliver them. This report examines tools and technologies that are driving real-time big data analytics.

Bayesian Statistics the Fun Way: Understanding Statistics and Probability with Star Wars, Lego, and Rubber Ducks


Will Kurt - 2019
    But many people use data in ways they don't even understand, meaning they aren't getting the most from it. Bayesian Statistics the Fun Way will change that.This book will give you a complete understanding of Bayesian statistics through simple explanations and un-boring examples. Find out the probability of UFOs landing in your garden, how likely Han Solo is to survive a flight through an asteroid shower, how to win an argument about conspiracy theories, and whether a burglary really was a burglary, to name a few examples.By using these off-the-beaten-track examples, the author actually makes learning statistics fun. And you'll learn real skills, like how to:- How to measure your own level of uncertainty in a conclusion or belief- Calculate Bayes theorem and understand what it's useful for- Find the posterior, likelihood, and prior to check the accuracy of your conclusions- Calculate distributions to see the range of your data- Compare hypotheses and draw reliable conclusions from themNext time you find yourself with a sheaf of survey results and no idea what to do with them, turn to Bayesian Statistics the Fun Way to get the most value from your data.

Bitcoin and Cryptocurrency Technologies: A Comprehensive Introduction


Arvind Narayanan - 2016
    Whether you are a student, software developer, tech entrepreneur, or researcher in computer science, this authoritative and self-contained book tells you everything you need to know about the new global money for the Internet age.How do Bitcoin and its block chain actually work? How secure are your bitcoins? How anonymous are their users? Can cryptocurrencies be regulated? These are some of the many questions this book answers. It begins by tracing the history and development of Bitcoin and cryptocurrencies, and then gives the conceptual and practical foundations you need to engineer secure software that interacts with the Bitcoin network as well as to integrate ideas from Bitcoin into your own projects. Topics include decentralization, mining, the politics of Bitcoin, altcoins and the cryptocurrency ecosystem, the future of Bitcoin, and more.An essential introduction to the new technologies of digital currencyCovers the history and mechanics of Bitcoin and the block chain, security, decentralization, anonymity, politics and regulation, altcoins, and much moreFeatures an accompanying website that includes instructional videos for each chapter, homework problems, programming assignments, and lecture slidesAlso suitable for use with the authors' Coursera online courseElectronic solutions manual (available only to professors)

Head First Data Analysis: A Learner's Guide to Big Numbers, Statistics, and Good Decisions


Michael G. Milton - 2009
    If your job requires you to manage and analyze all kinds of data, turn to Head First Data Analysis, where you'll quickly learn how to collect and organize data, sort the distractions from the truth, find meaningful patterns, draw conclusions, predict the future, and present your findings to others. Whether you're a product developer researching the market viability of a new product or service, a marketing manager gauging or predicting the effectiveness of a campaign, a salesperson who needs data to support product presentations, or a lone entrepreneur responsible for all of these data-intensive functions and more, the unique approach in Head First Data Analysis is by far the most efficient way to learn what you need to know to convert raw data into a vital business tool. You'll learn how to:Determine which data sources to use for collecting information Assess data quality and distinguish signal from noise Build basic data models to illuminate patterns, and assimilate new information into the models Cope with ambiguous information Design experiments to test hypotheses and draw conclusions Use segmentation to organize your data within discrete market groups Visualize data distributions to reveal new relationships and persuade others Predict the future with sampling and probability models Clean your data to make it useful Communicate the results of your analysis to your audience Using the latest research in cognitive science and learning theory to craft a multi-sensory learning experience, Head First Data Analysis uses a visually rich format designed for the way your brain works, not a text-heavy approach that puts you to sleep.