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Throughout Maya Angelou's life, from her childhood in Stamps, Arkansas, to her world travels as a bestselling writer, good food has played a central role. Preparing and enjoying homemade meals provides a sense of purpose and calm, accomplishment and connection. Now in "Hallelujah! The Welcome Table, Angelou shares memories pithy and poignant-and the recipes that helped to make them both indelible and irreplaceable. Angelou tells us about the time she was expelled from school for being afraid to speak-and her mother baked a delicious maple cake to brighten her spirits. She gives us her recipe for short ribs along with a story about a job she had as a cook at a Creole restaurant (never mind that she didn't know how to cook and had no idea what Creole food might entail). There was the time in London when she attended a wretched dinner party full of wretched people; but all wasn't lost-she did experience her initial taste of a savory onion tart. She recounts her very first night in her new home in Sonoma, California, when she invited M. F. K. Fisher over for cassoulet, and the evening Deca Mitford roasted a chicken when she was beyond tipsy-and created Chicken Drunkard Style. And then there was the hearty brunch Angelou made for a homesick Southerner, a meal that earned her both a job offer and a prophetic compliment: "If you can write half as good as you can cook, you are going to be famous." Maya Angelou is renowned in her wide and generous circle of friends as a marvelous chef. Her kitchen is a social center. From fried meat pies, chicken livers, and beef Wellington to caramel cake, bread pudding, and chocolate eclairs, the one hundred-plus recipes included here are all tried andtrue, and come from Angelou's heart and her home. "Hallelujah! The Welcome Table is a stunning collaboration between the two things Angelou loves best: writing and cooking.
New York Times bestselling author Pam Anderson updates her classic cookbook--which put "cooking by heart" on the map--to include modern flavors and new techniques that today's home cooks will love, with new and original full-color photographs. It's been 17 years since the blockbuster How to Cook Without a Book was published, and Pam Anderson's method of mastering easy techniques to create simple, delicious meals is even more relevant today. From the working professional who loves cooking to the busy family member trying to get dinner on the table, today's modern home cook wants to master useful techniques and know how to stock pantries and refrigerators to pull together delicious meals on the fly. Understanding that most recipes are simply "variations on a theme," Pam innovatively teaches technique, ultimately eliminating the need for recipes. The new edition will reflect ingredients and techniques home cooks love to use today: chicken dishes are revamped by using thighs instead of boneless skinless breasts; hearty, dark greens like kale and swiss chard replace hearts of Romaine in salads; roasted Brussels sprouts and sweet potatoes move from side dish to the main event in more meatless entrees; plus, tips for creating a whole meal using one pot or one sheet pan (instead of dirtying multiple dishes). Each chapter contains helpful at-a-glance charts that highlight the key points of every technique and a master recipe with enough variations to keep you going until you've learned how to cook without a book.
Data Mining: Practical Machine Learning Tools and Techniques, Third Edition, offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining. Thorough updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including new material on Data Transformations, Ensemble Learning, Massive Data Sets, Multi-instance Learning, plus a new version of the popular Weka machine learning software developed by the authors. Witten, Frank, and Hall include both tried-and-true techniques of today as well as methods at the leading edge of contemporary research. The book is targeted at information systems practitioners, programmers, consultants, developers, information technology managers, specification writers, data analysts, data modelers, database R&D professionals, data warehouse engineers, data mining professionals. The book will also be useful for professors and students of upper-level undergraduate and graduate-level data mining and machine learning courses who want to incorporate data mining as part of their data management knowledge base and expertise. Provides a thorough grounding in machine learning concepts as well as practical advice on applying the tools and techniques to your data mining projects Offers concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods Includes downloadable Weka software toolkit, a collection of machine learning algorithms for data mining tasks-in an updated, interactive interface. Algorithms in toolkit cover: data pre-processing, classification, regression, clustering, association rules, visualization