'It is important to say that Erdrich is one of the greatest living American writers, and LaRose is brilliant' Guardian 'Warm-hearted . . . a novel remarkable for its forgiveness and sheer magnanimity' Sunday Times Finalist for the 2016 National Books Critics Circle Award for Fiction In this literary masterwork, Louise Erdrich, the bestselling author of The Round House and the Pulitzer Prize nominee The Plague of Doves wields her breathtaking narrative magic in an emotionally haunting contemporary tale of a tragic accident, a demand for justice, and a profound act of atonement with ancient roots in Native American culture. Late summer in North Dakota, 1999: Landreaux Iron stalks a deer along the edge of the property bordering his own. He shoots with easy confidence but only when he staggers closer does he realise he has killed his neighbour's son. Dusty Ravich, the deceased boy, was best friends with Landreaux's five-year-old son, LaRose. The two families have been close for years and their children played together despite going to different schools. Landreaux is horrified at what he's done; fighting off his longstanding alcoholism, he ensconces himself in a sweat lodge and prays for guidance. And there he discovers an old way of delivering justice for the wrong he's done. The next day he and his wife Emmaline deliver LaRose to the bereaved Ravich parents. Standing on the threshold of the Ravich home, they say, 'Our son will be your son now'. LaRose is quickly absorbed into his new family. Gradually he's allowed visits with his birth family, whose grief for the son and brother they gave away mirrors that of the Raviches. The years pass and LaRose becomes the linchpin that links both families. As the Irons and the Raviches grow ever more entwined, their pain begins to subside. But when a man who nurses a grudge against Landreaux fixates on the idea that there was a cover-up the day Landreaux killed Dusty - and decides to expose this secret - he threatens the fragile peace between the two families...
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LaRose by Louise Erdrich | Summary & Analysis Preview: LaRose by Louise Erdrich is a novel about two little boys who are torn from their families and the infinite sorrow that’s left in their wake of their separations. As the repercussions of a tragic hunting accident unfold on a North Dakota reservation from 1999 to 2003, the narrative intermittently reaches back in time as far as 1839 to explore stories from the families’ Ojibwe heritage. Almost two hundred years’ worth of Ojibwe culture, American history, and family drama are brought to bear on the unusual situation of LaRose Iron, a five-year-old who handles an impossible situation with wisdom and grace. The central narrative starts off with a bang: Landreaux Iron, a skilled hunter, has shot his neighbors’ son. When five-year-old Dusty Ravich fell from his hiding place in a tree, he took a bullet that was meant for a deer. Landreaux is officially absolved of any wrongdoing; the shooting was… PLEASE NOTE: This is summary and analysis of the book and NOT the original book. Inside this Instaread Summary of LaRose: · Summary of the Book · Important People · Character Analysis · Analysis of the Themes and Author’s Style About the Author With Instaread, you can get the key takeaways, summary and analysis of a book in 15 minutes. We read every chapter, identify the key takeaways and analyze them for your convenience.
The field of data mining lies at the confluence of predictive analytics, statistical analysis, and business intelligence. Due to the ever-increasing complexity and size of data sets and the wide range of applications in computer science, business, and health care, the process of discovering knowledge in data is more relevant than ever before. This book provides the tools needed to thrive in today’s big data world. The author demonstrates how to leverage a company’s existing databases to increase profits and market share, and carefully explains the most current data science methods and techniques. The reader will “learn data mining by doing data mining”. By adding chapters on data modelling preparation, imputation of missing data, and multivariate statistical analysis, Discovering Knowledge in Data, Second Edition remains the eminent reference on data mining. The second edition of a highly praised, successful reference on data mining, with thorough coverage of big data applications, predictive analytics, and statistical analysis. Includes new chapters on Multivariate Statistics, Preparing to Model the Data, and Imputation of Missing Data, and an Appendix on Data Summarization and Visualization Offers extensive coverage of the R statistical programming language Contains 280 end-of-chapter exercises Includes a companion website for university instructors who adopt the book
After years of living a beige existence, Cat Larose, international color marketing expert, finally added a little color to her own life. All it took was a Paris sunset and a little red suitcase. Everyone wanted Cat's life. She had a handsome husband, a stylish home and a fascinating career as an international color-marketing consultant. Work took Cat to some of the world's most beautiful cities but something was missing: ironically, it was color. One day she found herself in Paris watching a sunset and, in a moment of clarity, she caught a glimpse of her sepia-toned future. When Cat got home, she did what she'd longed to do for years. She decided to paint her bedroom a magnificent Bordeaux red and put an end to her beige existence and her marriage. That was the beginning of a new life. Any Color but Beige is a bright, funny, genuine account of one woman's search for love in the deep end of the dating pool. None of the self-help books prepared Cat for the often funny, occasionally puzzling, sometimes sad but always colorful dating adventures with an international cast of frogs, princes and players. Cat makes the classic female mistake of thinking that love is a life preserver. Until one day she learns to swim.
MEDIA NOW, Eighth Edition, empowers you to think critically about the media and its effects on culture by providing a thorough understanding of how media technologies develop, operate, converge, and affect society. MEDIA NOW prepares you for encounters in the expanding fields of the Internet, interactive media, and traditional media industries through engaging, up-to-date material that covers the essential history, theories, concepts, and technical knowledge you need to thrive. Extensively updated in a new eighth edition, MEDIA NOW provides a comprehensive introduction to today's global media environment and ongoing developments in technology, culture, and critical theory that continue to transform this rapidly evolving industry and affect our daily lives. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.
Public Companies is designed to aid directors, officers and general counsel of public companies and those intending to go public.
Learn data science by doing data science! Data Science Using Python and R will get you plugged into the world’s two most widespread open-source platforms for data science: Python and R. Data science is hot. Bloomberg called data scientist “the hottest job in America.” Python and R are the top two open-source data science tools in the world. In Data Science Using Python and R, you will learn step-by-step how to produce hands-on solutions to real-world business problems, using state-of-the-art techniques. Data Science Using Python and R is written for the general reader with no previous analytics or programming experience. An entire chapter is dedicated to learning the basics of Python and R. Then, each chapter presents step-by-step instructions and walkthroughs for solving data science problems using Python and R. Those with analytics experience will appreciate having a one-stop shop for learning how to do data science using Python and R. Topics covered include data preparation, exploratory data analysis, preparing to model the data, decision trees, model evaluation, misclassification costs, naïve Bayes classification, neural networks, clustering, regression modeling, dimension reduction, and association rules mining. Further, exciting new topics such as random forests and general linear models are also included. The book emphasizes data-driven error costs to enhance profitability, which avoids the common pitfalls that may cost a company millions of dollars. Data Science Using Python and R provides exercises at the end of every chapter, totaling over 500 exercises in the book. Readers will therefore have plenty of opportunity to test their newfound data science skills and expertise. In the Hands-on Analysis exercises, readers are challenged to solve interesting business problems using real-world data sets.
Learn methods of data analysis and their application to real-world data sets. Offers comprehensive coverage of association rules, clustering, neural networks, logistic regression, multivariate analysis, and R statistical programming language Features over 750 chapter exercises, allowing readers to assess their understanding of the new material Provides a detailed case study that brings together the lessons learned in the book Includes access to the companion website, www.dataminingconsultant, with exclusive password-protected instructor content