Mark fenner (74 resultados)

Paperback. Condición: Good. 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.…

Condición: good. The book is in good condition with all pages and cover intact, including the dust jacket if originally issued. The spine may show light wear. Pages may contain some notes or highlighting, and there might be a "From the library of" label. Boxed set packaging, shrink wrap, or included media like CDs may be missing.…

Paperback. Condición: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less. Lamoureaux, Mikki (ilustrador).

Paperback. Condición: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority.

Paperback. Condición: Fair. 1. The item might be beaten up but readable. May contain markings or highlighting, as well as stains, bent corners, or any other major defect, but the text is not obscured in any way.

Paperback. Condición: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.

paperback. Condición: Good. 1st Edition. Ships in a BOX from Central Missouri! May not include working access code. Will not include dust jacket. Has used sticker(s) and some writing or highlighting. UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).

Paperback. Condición: Very Good. 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.…

Condición: 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.…

Condición: New. pp. 504.

Soft cover. Condición: New. ISBN:9789353944902,Territorial restriction maybe printed on the book. This is an Int'l edition, ISBN and cover may differ from US edition, Contents same as US edition.

Paperback. Condición: new. New Copy. Customer Service Guaranteed.

Condición: New. Brand New. Soft Cover International Edition. Different ISBN and Cover Image. Priced lower than the standard editions which is usually intended to make them more affordable for students abroad. The core content of the book is generally the same as the standard edition. The country selling restrictions may be printed on the book but is no problem for the self-use. This Item maybe shipped from US or any other country as we have multiple locations worldwide.…

Paperback. Condición: Brand New. 29 pages. 9.00x6.00x0.07 inches. In Stock.

Condición: New. Brand New, Softcover edition. This item may ship from the US or our Overseas warehouse depending on your location and stock availability.

Condición: New.

Condición: New. Brand New! Not Overstocks or Low Quality Book Club Editions! Direct From the Publisher! We're not a giant, faceless warehouse organization! We're a small town bookstore that loves books and loves it's customers! Buy from Lakeside Books.

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

Condición: New.

Hardcover. Condición: New. Estado de la sobrecubierta: 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.…

Condición: As New. Unread book in perfect condition.

Paperback. Condición: 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.…

Condición: As New. Unread book in perfect condition.

Paperback. Condición: New Books. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 6-10 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability. …

Condición: New.

Condición: New.

Paperback. Condición: New. Humans make mistakes. Many of us lose career ascendency or risk destroying our institutions by doubling down on or ignoring outcomes of our own poor decisions.Good leaders learn and teach from their errors. Professions are strengthened. Institutions thrive. Careers grow.Through real-life stories that focus on senior/board leadership from multiple walks of life, and brief discussions of significant attributes, readers will be challenged to diagnose and turn missteps into positive growth experiences.The authors of this book have had extensive careers in public and private, for-profit and not-for-profit settings, and in independent and government-sponsored consulting, development, academic, and clinical environments. Without having any single leadership paradigm to push, they raise questions about outcomes for institutions that are affected and individual career paths.Their cautionary tales ask readers to think through "next steps" or prevent the need to get there; hence, this is an ideal extra-assignment book in graduate management courses and for managers seeking to work their way up toward higher leadership roles. Board members also can learn from its non-industry-specific target readership.…

Condición: 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.…

Condición: New.

Paperback. Condición: 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.…