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Shortlisted as the Irish Cookbook of the Year at the 2013 Bord Gais Energy Irish Book Awards Everybody loves the weekend. It's time to kick off your shoes, let your hair down and enjoy the good things in life: friends, family - and good food. In her fantastic new book, award-winning Catherine Fulvio celebrates the relaxed and easy vibe of the weekend with 100 new recipes to take you from Friday to Sunday in style. From Friday night curry to Saturday brunch, from rainy-day baking, to Sunday's family dinner. If weekday breakfasts consist of a quick bowl of cereal before running out the door, now's the time for Chocolate French Toast with Hazelnuts and Raspberries. If mid-week meals consist of express rice and fast food, why not host a Tapas night and make Garlic Artichokes and Mushrooms, Roasted Grapes with Jamon Serrano and Patatas Bravas? If you depend on a vending machine for a weekday snack, how about an afternoon of baking - try the Chocolate and Cardamom Brioche Buns or Orange and Almond Polenta Squares. So forget about work. Forget about express meals. Close the door, turn the music on, fire up the cooker - it's the weekend! 'The Weekend Chef brings a more relaxed attitude to cooking at the weekend, with easily prepared meals in abundance. ' Hotel and Restaurant Review

Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. The aim of this textbook is to introduce machine learning, and the algorithmic paradigms it offers, in a principled way. The book provides a theoretical account of the fundamentals underlying machine learning and the mathematical derivations that transform The Weekend Chef: Easy Food for Lazy Days free ebook these principles into practical algorithms. Following a presentation of the basics, the book covers a wide array of central topics unaddressed by previous textbooks. These include a discussion of the computational complexity of learning and the concepts of convexity and stability; important algorithmic paradigms including stochastic gradient descent, neural networks, and structured output learning; and emerging theoretical concepts such as the PAC-Bayes approach and compression-based bounds. Designed for advanced undergraduates or beginning graduates, the text makes the fundamentals and algorithms of machine learning accessible to students and non-expert readers in statistics, computer science, mathematics and engineering.

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Author: Catherine Fulvio
Number of Pages: 224 pages
Published Date: 15 Jan 2014
Publisher: Gill & Macmillan Ltd
Publication Country: Dublin, Ireland
Language: English
ISBN: 9780717158614
Download Link: Click Here
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