Written expressly for "anyone who believes there are big questions out there, but does not know how to approach them," Think provides a sound framework for exploring the most basic themes of philosophy, and for understanding how major philosophers have tackled the questions that have pressed themselves most forcefully on human consciousness.

    Alexander 'Sandy' Mackendrick directed classic Ealing comedies plus a Hollywood masterpiece, Sweet Smell of Success. But after retiring from film-making in 1969, he then spent nearly 25 years teaching his craft at the California Institute of the Arts in Los Angeles.Mackendrick produced hundreds of pages of masterly handouts and sketches, designed to guide his students to a finer understanding of how to write a story, and then use those devices peculiar to cinema in order to tell that story as effectively as possible. Gathered and edited in this collection, Mackendrick's teachings reveal that he had the talent not only to make great films, but also to articulate the process with a clarity and insight that will still inspire any aspirant film-maker.

    Ordinary art. Ordinary art means something like: all art not made by Mozart. After all, art is rarely made by Mozart-like people; essentially-statistically speaking-there aren't any people like that. Geniuses get made once-a-century or so, yet good art gets made all the time, so to equate the making of art with the workings of genius removes this intimately human activity to a strangely unreachable and unknowable place. For all practical purposes making art can be examined in great detail without ever getting entangled in the very remote problems of genius."--from the Introduction

    Now, James Monaco offers a revised and rewritten third edition incorporating every major aspect of this dynamic medium right up to the present.Looking at film from many vantage points, How to Read a Film: Movies, Media, Multimedia explores the medium as both art and craft, sensibility and science, tradition and technology. After examining film's close relation to such other narrative media as the novel, painting, photography, television, and even music, Monaco discusses those elements necessary to understand how films convey meaning and, more importantly, how we can best discern all that a film is attempting to communicate.In a key departure from the book's previous editions, the new and still-evolving digital context of film is now emphasized throughout How to Read a Film. A new chapter on multimedia brings media criticism into the twenty-first century with a thorough discussion of topics like virtual reality, cyberspace, and the proximity of both to film. Monaco has likewise doubled the size and scope of his Film and Media: A Chronology appendix. The book also features a new introduction, an expanded bibliography, and hundreds of illustrative black-and-white film stills and diagrams. It is a must for all film students, media buffs, and movie fans.

    Now, in his most comprehensive book yet on the topic, Buzan reveals exciting new ways to improve one's memory, concentration, creativity, ability to learn, and more.

    It is a book that models the types of issues that best suit different approaches and allows students to understand when to use mixed methods. Furthermore, its focus on theory and paradigms is done in a way that helps students decode their meaning." --MARTHA MONTERO-SIEBURTH, University of Massachusetts, BostonNew to the Second Edition:Because mixed methods research has come into its own since the publication of the first edition, every chapter now shows how to implement a mixed methods design in your proposal or plan as well as showing how to implement qualitative and quantitative approaches Ethical issues that may arise in quantitative, qualitative and mixed methods designs have been added to a new section in Chapter 3 Writing tips and considerations have been expanded and moved to the first part of the book to get your research plan started in the right direction The latest developments in qualitative inquiry, including advocacy, participatory, and emancipatory approaches have been added to Chapter 10 Mixed methods procedures (Chapter 11) show readers how to identify types of mixed methods strategy, select data collection and analysis approaches, and plan the overall structure of the study

    It will enable making a design for almost any kind of building, or any part of the built environment. ‘Patterns,’ the units of this language, are answers to design problems: how high should a window sill be?; how many stories should a building have?; how much space in a neighborhood should be devoted to grass and trees?More than 250 of the patterns in this language are outlined, each consisting of a problem statement, a discussion of the problem with an illustration, and a solution. As the authors say in their introduction, many of the patterns are archetypal, so deeply rooted in the nature of things that it seems likely that they will be a part of human nature and human action as much in five hundred years as they are today.A Pattern Language is related to Alexander’s other works in the Center for Environmental Structure series: The Timeless Way of Building (introductory volume) and The Oregon Experiment.

    The Essential Guide to Rhetoric provides an accessible and balanced overview of the core historical and contemporary theories. It uses concrete, relevant examples and jargon-free language to bring these concepts to life. The guide helps students move from concept to action with discussions of invention, the traditions of trope, argument and speech, among others. This handy guide is an excellent addition to the public speaking class, extending and deepening crucial concepts, and an indispensable supplement to the rhetorical theory class.

    Data Science For Dummies is the perfect starting point for IT professionals and students interested in making sense of their organization’s massive data sets and applying their findings to real-world business scenarios. From uncovering rich data sources to managing large amounts of data within hardware and software limitations, ensuring consistency in reporting, merging various data sources, and beyond, you’ll develop the know-how you need to effectively interpret data and tell a story that can be understood by anyone in your organization. Provides a background in data science fundamentals before moving on to working with relational databases and unstructured data and preparing your data for analysis Details different data visualization techniques that can be used to showcase and summarize your data Explains both supervised and unsupervised machine learning, including regression, model validation, and clustering techniques Includes coverage of big data processing tools like MapReduce, Hadoop, Dremel, Storm, and Spark It’s a big, big data world out there – let Data Science For Dummies help you harness its power and gain a competitive edge for your organization.

    'Asking the Right Questions' helps students bridge the gap between simply memorising or blindly accepting information, and the greater challenge of critical analysis and synthesis.

    Now that machine learning is thriving, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn how to use a range of techniques, starting with simple Linear Regression and progressing to Deep Neural Networks. If you have some programming experience and you’re ready to code a machine learning project, this guide is for you.This hands-on book shows you how to use:Scikit-Learn, an accessible framework that implements many algorithms efficiently and serves as a great machine learning entry pointTensorFlow, a more complex library for distributed numerical computation, ideal for training and running very large neural networksPractical code examples that you can apply without learning excessive machine learning theory or algorithm details

    Major retailers are predicting everything from when their customers are pregnant to when they want a new pair of Chuck Taylors. It's a brave new world where seemingly meaningless data can be transformed into valuable insight to drive smart business decisions.But how does one exactly do data science? Do you have to hire one of these priests of the dark arts, the "data scientist," to extract this gold from your data? Nope.Data science is little more than using straight-forward steps to process raw data into actionable insight. And in Data Smart, author and data scientist John Foreman will show you how that's done within the familiar environment of a spreadsheet. Why a spreadsheet? It's comfortable! You get to look at the data every step of the way, building confidence as you learn the tricks of the trade. Plus, spreadsheets are a vendor-neutral place to learn data science without the hype. But don't let the Excel sheets fool you. This is a book for those serious about learning the analytic techniques, the math and the magic, behind big data.Each chapter will cover a different technique in a spreadsheet so you can follow along: - Mathematical optimization, including non-linear programming and genetic algorithms- Clustering via k-means, spherical k-means, and graph modularity- Data mining in graphs, such as outlier detection- Supervised AI through logistic regression, ensemble models, and bag-of-words models- Forecasting, seasonal adjustments, and prediction intervals through monte carlo simulation- Moving from spreadsheets into the R programming languageYou get your hands dirty as you work alongside John through each technique. But never fear, the topics are readily applicable and the author laces humor throughout. You'll even learn what a dead squirrel has to do with optimization modeling, which you no doubt are dying to know.

    We have Mindstorms to thank for that. In this book, pioneering computer scientist Seymour Papert uses the invention of LOGO, the first child-friendly programming language, to make the case for the value of teaching children with computers. Papert argues that children are more than capable of mastering computers, and that teaching computational processes like de-bugging in the classroom can change the way we learn everything else. He also shows that schools saturated with technology can actually improve socialization and interaction among students and between students and teachers.

    Professor Barsam's clear writing, thorough presentation of fundamental film principles, and unique pedagogical additions to the traditional introductory text-- including an entire chapter devoted to analytical writing-- ensure that students approach screenings and writing assignments equipped with the analytical tools necessary to be active, insightful interpreters of movies. "Looking at Movies" is accompanied by two outstanding multimedia resources, the Student website and CD-ROM, both of which are integrated directly with the text.

    The second volume in The Traditional Bowyer's Bible series covers ancient European bows, Eastern Woodland bows, recurves, strings, steel points, quivers, and much more.