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We all know the basics of punctuation. Or do we? A look at most neighborhood signage tells a different story. Through sloppy usage and low standards on the internet, in email, and now text messages, we have made proper punctuation an endangered species. In Eats, Shoots & Leaves, former editor Lynne Truss dares to say, in her delightfully urbane, witty, and very English way, that it is time to look at our commas and semicolons and see them as the wonderful and necessary things they are. This is a book for people who love punctuation and get upset when it is mishandled. From the invention of the question mark in the time of Charlemagne to George Orwell shunning the semicolon, this lively history makes a powerful case for the preservation of a system of printing conventions that is much too subtle to be mucked about with.
How do language and thought connect to things in the world? John Hawthorne and David Manley offer an original and ambitious treatment of the semantic phenomenon of reference and the cognitive phenomenon of singular thought, leading to a new unified account of definite and indefinite descriptions, names, and demonstratives.
A revised, enlarged, and updated edition of this authoritative and entertaining reference book —named the #2 essential home library reference book by the Wall Street Journal “Shapiro does original research, earning [this] volume a place on the quotation shelf next to Bartlett's and Oxford's.”—William Safire, New York Times Magazine (on the original edition) “A quotations book with footnotes that are as fascinating to read as the quotes themselves.”—Arthur Spiegelman, Washington Post Book World (on the original edition) Updated to include more than a thousand new quotations, this reader-friendly volume contains over twelve thousand famous quotations, arranged alphabetically by author and sourced from literature, history, popular culture, sports, digital culture, science, politics, law, the social sciences, and all other aspects of human activity. Contemporaries added to this edition include Beyoncé, Sandra Cisneros, James Comey, Drake, Louise Glück, LeBron James, Brett Kavanaugh, Lady Gaga, Lin-Manuel Miranda, Barack Obama, John Oliver, Nancy Pelosi, Vladimir Putin, Bernie Sanders, Donald Trump, and David Foster Wallace. The volume also reflects path-breaking recent research resulting in the updating of quotations from the first edition with more accurate wording or attribution. It has also incorporated noncontemporary quotations that have become relevant to the present day. In addition, The New Yale Book of Quotations reveals the striking fact that women originated many familiar quotations, yet their roles have been forgotten and their verbal inventions have often been credited to prominent men instead. This book’s quotations, annotations, extensive cross-references, and large keyword index will satisfy both the reader who seeks specific information and the curious browser who appreciates an amble through entertaining pages.
A comprehensive reference for writers of mysteries, thrillers, action/adventure, true crime, police procedurals, romantic suspense, and psychological mysteries--whether novels or scripts--covering numerous aspects of crime, outlining general rules of thumb, as well as specific policies and procedures of various law enforcement agencies. Annotation copyright by Book News, Inc., Portland, OR
"Provides information about librarianship as a career, including types of libraries, types of jobs within libraries, professional issues, and educational requirements"--Provided by publisher.
An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.
The Publication Manual of the American Psychological Association is the style manual of choice for writers, editors, students, and educators in the social and behavioral sciences, nursing, education, business, and related disciplines.