The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be constructed and then manipulated by reasoning algorithms. These models can also be learned automatically from data, allowing the approach to be used in cases where manually constructing a model is difficult or even impossible. Because uncertainty is an inescapable aspect of most real-world applications, the book focuses on probabilistic models, which make the uncertainty explicit and provide models that are more faithful to reality.Probabilistic Graphical Models discusses a variety of models, spanning Bayesian networks, undirected Markov networks, discrete and continuous models, and extensions to deal with dynamical systems and relational data. For each class of models, the text describes the three fundamental cornerstones: representation, inference, and learning, presenting both basic concepts and advanced techniques. Finally, the book considers the use of the proposed framework for causal reasoning and decision making under uncertainty. The main text in each chapter provides the detailed technical development of the key ideas. Most chapters also include boxes with additional material: skill boxes, which describe techniques; case study boxes, which discuss empirical cases related to the approach described in the text, including applications in computer vision, robotics, natural language understanding, and computational biology; and concept boxes, which present significant concepts drawn from the material in the chapter. Instructors (and readers) can group chapters in various combinations, from core topics to more technically advanced material, to suit their particular needs.

    It takes a truly objects first approach to teaching problem solving using Java. These are complicated concepts so the book uses the development environment BlueJ to help the student's understanding. BlueJ has a strong emphasis on visualization and interaction techniques, and allows the students to manipulate objects and call methods as a first exercise. BlueJ is free and freely available, and has been developed specifically for teaching. The book is loaded with projects so that the student can really get a grip on actually solving problems; and it takes a spiral approach , introducing a topic in a simple context early on, then revisiting it later in the book to deepen understanding. It also comes with a CD containing JDK, BlueJ, a BlueJ tutorial and code for all the projects. The website contains style guide for all examples, PowerPoints for lecturers and also a Solutions Manual.

    A step-by-step visual journey through the mathematics of neural networks, and making your own using Python and Tensorflow.

    Its techniques are widely applied in engineering, science, finance, and commerce. This book is designed for a short course on machine learning. It is a short course, not a hurried course. From over a decade of teaching this material, we have distilled what we believe to be the core topics that every student of the subject should know. We chose the title `learning from data' that faithfully describes what the subject is about, and made it a point to cover the topics in a story-like fashion. Our hope is that the reader can learn all the fundamentals of the subject by reading the book cover to cover. ---- Learning from data has distinct theoretical and practical tracks. In this book, we balance the theoretical and the practical, the mathematical and the heuristic. Our criterion for inclusion is relevance. Theory that establishes the conceptual framework for learning is included, and so are heuristics that impact the performance of real learning systems. ---- Learning from data is a very dynamic field. Some of the hot techniques and theories at times become just fads, and others gain traction and become part of the field. What we have emphasized in this book are the necessary fundamentals that give any student of learning from data a solid foundation, and enable him or her to venture out and explore further techniques and theories, or perhaps to contribute their own. ---- The authors are professors at California Institute of Technology (Caltech), Rensselaer Polytechnic Institute (RPI), and National Taiwan University (NTU), where this book is the main text for their popular courses on machine learning. The authors also consult extensively with financial and commercial companies on machine learning applications, and have led winning teams in machine learning competitions.

    The authors explain each category of vulnerability using real-world examples, screen shots and code extracts. The book is extremely practical in focus, and describes in detail the steps involved in detecting and exploiting each kind of security weakness found within a variety of applications such as online banking, e-commerce and other web applications. The topics covered include bypassing login mechanisms, injecting code, exploiting logic flaws and compromising other users. Because every web application is different, attacking them entails bringing to bear various general principles, techniques and experience in an imaginative way. The most successful hackers go beyond this, and find ways to automate their bespoke attacks. This handbook describes a proven methodology that combines the virtues of human intelligence and computerized brute force, often with devastating results.The authors are professional penetration testers who have been involved in web application security for nearly a decade. They have presented training courses at the Black Hat security conferences throughout the world. Under the alias "PortSwigger," Dafydd developed the popular Burp Suite of web application hack tools.

    However, these activities can be viewed as two facets of the same field, and together they have undergone substantial development over the past ten years. In particular, Bayesian methods have grown from a specialist niche to become mainstream, while graphical models have emerged as a general framework for describing and applying probabilistic models. Also, the practical applicability of Bayesian methods has been greatly enhanced through the development of a range of approximate inference algorithms such as variational Bayes and expectation propagation. Similarly, new models based on kernels have had a significant impact on both algorithms and applications. This new textbook reflects these recent developments while providing a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first-year PhD students, as well as researchers and practitioners, and assumes no previous knowledge of pattern recognition or machine learning concepts. Knowledge of multivariate calculus and basic linear algebra is required, and some familiarity with probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.

    

     Beginning with her solitary childhood in London, it took years for Melanie Phillips to understand her parents’ emotional frailties and even longer to escape from them. But Phillips inherited her family’s strong Jewish values and a passionate commitment to freedom from oppression. It was this moral foundation that ultimately turned her against the warped and tyrannical attitudes of the Left, requiring her to break away not only from her parents—but also from the people she had seen as her wider political family. Through her poignant story of transformation and separation, we gain insight into the political uproar that has engulfed the West. Britain’s vote to leave the EU, the rise of far-Right political parties in Europe, and the stunning election of US president Donald Trump all involve a revolt against the elites by millions. It is these disdained masses who have been championed by Melanie Phillips in a career as prescient as it has been provocative. Guardian Angel is not only an affecting personal story, but it provides a vital explanation why the West is at a critical crossroads today. “Melanie Phillips has been one of the brave and necessary voices of our time, unafraid to speak the language of moral responsibility in an age of obfuscation and denial. This searing account of her personal journey is compelling testimony to her courage in speaking truth to power.”—Rabbi Lord Jonathan Sacks

    Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools.Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python.With this handbook, you’ll learn how to use: * IPython and Jupyter: provide computational environments for data scientists using Python * NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python * Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python * Matplotlib: includes capabilities for a flexible range of data visualizations in Python * Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms

    I’m definitely having a midlife crisis…I didn’t expect to be single at forty-five, but I’ve always prided myself on facing up to a challenge. A new town, a better job, and a cozy cottage of my own are all at the top of my To Do list. A new man? Right at the bottom. I’m far too busy for love.Returning to the Devon village of Crows Tor on Dartmoor brings a new lease of life for me – in more ways than one. It turns out my old school friend, Fiona, makes a secret moonshine at her whisky distillery using spring water collected under the full moon. Apparently it enhances your psychic powers, and she tempts me to have a shot… or three.I’m thrilled at the prospect of developing my psychic abilities. And then I look into a crystal ball at the May Day fair and have a vision of a murder. Suddenly it’s not such a fun idea after all, especially when my prediction comes true. Consumed by guilt because I didn’t warn the victim, I’m determined to find the killer, even if it puts me in the very path of danger…*The Midlife Moonshine stories are set on Dartmoor in Devon, England, and contain British English spelling and usage. They are clean reads with no graphic violence, strong language, or sex, but they’re packed with magic, mystery, romance, and history – all starring women in the prime of midlife!

    Richard Coles, led a pilgrimage to all the major historic sites of the Holy Land: from Nazareth and the Sea of Galilee in the North, via Jericho and the Jordan River, to Bethlehem and, finally, Jerusalem. All of the pilgrims in his care were practising Christians, except one: the writer Kevin Jackson, a diffident and sympathetic atheist intrigued by the chance to take part in this modern-day version of an ancient act of piety, and to learn some more about his old friend, the media clergyman.Coles to Jerusalem is Kevin Jackson’s light-hearted diary of that pilgrimage, and a close-up portrait of Richard Coles both as priest and as man. As the journey proceeds, Coles reminisces at length about his past life as a rock star and radical gay agitator, his new life as a spiritual leader and a popular broadcaster on BBC radio and television, and the strange, unpredictable path that led him from self-destructive debauchery to faith and vocation.With a lively supporting cast of fellow pilgrims, Coles to Jerusalem ranges among the magnificence of ancient monuments and the banalities of the guided tour, the grim political background of contemporary Israel and the comedy of a group of idiosyncratic English folk abroad, the intensity of worship and the lightness of banter. It will be irresistible to all admirers of Richard Coles, who has contributed a foreword; and a revelation to those who have never encountered his wisdom and warmth.

    This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree- based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

    Swift builds on the best of C and Objective-C, without the constraints of C compatibility. Swift adopts safe programming patterns and adds modern features to make programming easier, more flexible, and more fun. Swift’s clean slate, backed by the mature and much-loved Cocoa and Cocoa Touch frameworks, is an opportunity to reimagine how software development works.

    This Fourth Edition not only keeps this tradition alive, it actually improves on it."--Steve Vinoski, Chief Engineer, Product Innovation, IONA Technologies" The Primer really brings this large and complex language down to size."--Justin Shaw, Senior Member of Technical Staff, Electronic Programs Division, The Aerospace Corporation"It not only gets novices up and running early, but gets them to do so using good programming practices."--Nevin ": -)" Liber, Senior Principal Engineer (C++ developer since 1988)This popular tutorial introduction to standard C++ has been completely updated, reorganized, and rewritten to help programmers learn the language faster and use it in a more modern, effective way.Just as C++ has evolved since the last edition, so has the authors' approach to teaching it. They now introduce the C++ standard library from the beginning, giving readers the means to write useful programs without first having to master every language detail. Highlighting today's best practices, they show how to write programs that are safe, can be built quickly, and yet offer outstanding performance. Examples that take advantage of the library, and explain the features of C++, also show how to make the best use of the language. As in its previous editions, the book's authoritative discussion of fundamental C++ concepts and techniques makes it a valuable resource even for more experienced programmers.Program Faster and More Effectively with This Rewritten ClassicRestructured for quicker learning, using the C++ standard libraryUpdated to teach the most current programming styles and program design techniquesFilled with new learning aids that emphasize important points, warn about common pitfalls, suggest good programming practices, and provide general usage tipsComplete with exercises that reinforce skills learnedAuthoritative and comprehensive in its coverage The source code for the book's extended examples is available on the Web at the address below.www.awprofessional.com/cpp_primer

    The book helps psychologists apply the Ethics Code to the constantly changing scientific, professional, and legal realities of the discipline. Author Celia B. Fisher addresses the revised format, choice of wording, aspirational rationale, and enforceability of the code and puts these changes into practical perspective for psychologists. The book provides in-depth discussions of the foundation and application of each ethical standard to the broad spectrum of scientific, teaching, and professional roles of psychologists. This unique guide helps psychologists effectively use ethical principles and standards to morally conduct their work activities, avoid ethical violations, and, most importantly, preserve and protect the fundamental rights and welfare of those whom they serve.