Mark fenner (72 Ergebnisse)

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Moving Pictures, Migrating Identities
Rueschmann, Eva; & Angelica Fenner, Norman S. Holland, Mark Ingram, Adam Knee, Florence Martin, Allen Meek, Eva Rueschmann, Kenneth Womack, Barton Byg, David N. Coury, Todd F. Davis, Rodica Diaconescu-Blumenfeld, Carolyn Durham
- Hardcover
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Hardcover. Zustand: New. Zustand des Schutzumschlags: New. First Printing of the First Edition. Jackson: University Press of Mississippi, 2003. BRAND NEW in a BRAND NEW dust jacket. Perfect condition. NO chips. NO tears. NO creases. NO rubbing. NO fading. Sharp corners. Bright, shiny, clean, square and tight. NO owner's name or…bookplate. NOT a remainder. 2003. First Edition, First Printing with complete number row (4321) on the copyright page. With contributions by Angelica Fenner, Norman S. Holland, Mark Ingram, Adam Knee, Florence Martin, Allen Meek, Eva Rueschmann, Kenneth Womack, Barton Byg, David N. Coury, Todd F. Davis, Rodica Diaconescu-Blumenfeld, Carolyn Durham, Mine Eren, and Catherine Wynne. Photo illustrated. List of chapter notes. Bibliography. Index. Bound in the original gray cloth, stamped in black on the spine. From the dust jacket: "In recent decades the experiences and political struggles of immigrants, exiles, and sojourners have inspired some of the most provocative feature films and documentaries in world cinema. These have sparked theoretical debates about cultural identity, place, and representation in the media. The thirteen essays in this anthology contribute to a growing interest in the emerging international genre of exile and diaspora films, treating a variety of motion pictures from Europe and the United States in their national and transnational contexts. These essays examine how contemporary cinema -- both fiction feature film and documentary -- has imagined the experience of migration and displacement, the struggle for citizenship and cultural belonging, and the encounter and negotiation of different cultures and identities. The authors discuss the ways cinema explores the many contradictions of exile and diaspora -- the complicated meanings of home, the exile's nostalgia for origins, the hopes and tragedies of border crossings, the difficulties of belonging to a strange society and being a stranger, and the conundrums of gender for the migrant, especially women's conciliation of different social roles and cultural expectations. Included are discussions of such well known films as THE CRYING GAME, LAMERICA, JOURNEY OF HOPE, EXOTICA, CHOCOLAT, LONE STAR, and FLYING DOWN TO RIO, as well as smaller productions by diasporic or immigrant filmmakers who deserve critical attention, including Seyhan Derin's I'M MY MOTHER'S DAUGHTER, Mina Shum's DOUBLE HAPPINESS, and Yanina Benguigui's IMMIGRANT MEMORIES: MAGHREBI HERITAGE. Encompassing different models of intercultural theory, this collection draws on the fields of anthropology, political economy, production and reception studies, feminism, travel writing, and postcolonial criticism and captures the complex, diverse, and continually changing body of diaspora film and its intertextual connections. Eva Rueschmann is an assistant professor of cultural studies at Hampshire College, the author of SISTERS ON THE SCREEN: SIBLINGS IN CONTEMPORARY CINEMA, and a contributor to two anthologies, INTERNATIONAL WOMEN'S WRITING: NEW LANDSCAPES OF IDENTITIES and THE SIGNIFICANCE OF SIBLING RELATIONSHIPS IN LITERATURE.". First Printing of the First Edition. Hardcover. New/New. 8vo. xxx, 265pp. Great Packaging, Fast Shipping.

- Softcover
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Paperback. Zustand: New. The Complete Beginner's Guide to Understanding and Building Machine Learning Systems with Python Machine Learning with Python for Everyone will help you master the processes, patterns, and strategies you need to build effective learning systems, even if you're an absolute beginner. If you can write some…Python code, this book is for you, no matter how little college-level math you know. Principal instructor Mark E. Fenner relies on plain-English stories, pictures, and Python examples to communicate the ideas of machine learning. Mark begins by discussing machine learning and what it can do; introducing key mathematical and computational topics in an approachable manner; and walking you through the first steps in building, training, and evaluating learning systems. Step by step, you'll fill out the components of a practical learning system, broaden your toolbox, and explore some of the field's most sophisticated and exciting techniques. Whether you're a student, analyst, scientist, or hobbyist, this guide's insights will be applicable to every learning system you ever build or use. Understand machine learning algorithms, models, and core machine learning conceptsClassify examples with classifiers, and quantify examples with regressorsRealistically assess performance of machine learning systemsUse feature engineering to smooth rough data into useful formsChain multiple components into one system and tune its performanceApply machine learning techniques to images and textConnect the core concepts to neural networks and graphical modelsLeverage the Python scikit-learn library and other powerful tools Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.

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Paperback or Softback. Zustand: New. Machine Learning with Python for Everyone. Book.

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Zustand: good. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers.

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Paperback. Zustand: New. The Complete Beginner's Guide to Understanding and Building Machine Learning Systems with Python Machine Learning with Python for Everyone will help you master the processes, patterns, and strategies you need to build effective learning systems, even if you're an absolute beginner. If you can write some…Python code, this book is for you, no matter how little college-level math you know. Principal instructor Mark E. Fenner relies on plain-English stories, pictures, and Python examples to communicate the ideas of machine learning. Mark begins by discussing machine learning and what it can do; introducing key mathematical and computational topics in an approachable manner; and walking you through the first steps in building, training, and evaluating learning systems. Step by step, you'll fill out the components of a practical learning system, broaden your toolbox, and explore some of the field's most sophisticated and exciting techniques. Whether you're a student, analyst, scientist, or hobbyist, this guide's insights will be applicable to every learning system you ever build or use. Understand machine learning algorithms, models, and core machine learning conceptsClassify examples with classifiers, and quantify examples with regressorsRealistically assess performance of machine learning systemsUse feature engineering to smooth rough data into useful formsChain multiple components into one system and tune its performanceApply machine learning techniques to images and textConnect the core concepts to neural networks and graphical modelsLeverage the Python scikit-learn library and other powerful tools Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.

- Softcover
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Paperback. Zustand: new. Paperback. Machine Learning with Python for Everyone will help you master the processes, patterns, and strategies you need to build effective learning systems, even if you're an absolute beginner. If you can write some Python code, this book is for you, no matter how little college-level math you know. P…rincipal instructor Mark E. Fenner relies on plain-English stories, pictures, and Python examples to communicate the ideas of machine learning. Mark begins by discussing machine learning and what it can do; introducing key mathematical and computational topics in an approachable manner; and walking you through the first steps in building, training, and evaluating learning systems. Step by step, you'll fill out the components of a practical learning system, broaden your toolbox, and explore some of the field's most sophisticated and exciting techniques. Whether you're a student, analyst, scientist, or hobbyist, this guide's insights will be applicable to every learning system you ever build or use. SamplesPreview sample pages from Machine Learning with Python for Everyone > Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Zustand: New. 1st edition NO-PA16APR2015-KAP.