Author: Publisher:
ISBN:
Category : Cooking
Languages : en
Pages : 416
Book Description
Cooking Light Annual Recipes
Author: Southern Living 1988 Annual Recipes
Author: Southern LivingPublisher: Oxmoor House
ISBN: 9780848707330
Category : Cooking
Languages : en
Pages : 360
Book Description
Recipes from Southern Living Magazine.
Southern Living Annual Recipes Cookbook
Author: Southern LivingPublisher: Oxmoor House
ISBN: 9780848716882
Category : Cooking
Languages : en
Pages : 432
Book Description
Offers over 1500 recipes taken from the annual editions of the Southern Living cookbook series.
Annual Report 2002
Author: Publisher: Bioversity International
ISBN: 9290435917
Category :
Languages : en
Pages : 44
Book Description
Cooking Light Annual Recipes 2014
Author: Editors of Cooking Light MagazinePublisher: Time Home Entertainment
ISBN: 0848743938
Category : Cooking
Languages : en
Pages : 1931
Book Description
Country Home
Author: Cooking Light Annual Recipes 2013
Author: Editors of Cooking Light MagazinePublisher: Time Home Entertainment
ISBN: 0848741811
Category : Cooking
Languages : en
Pages : 1507
Book Description
"All the appetizing and inspiring recipes from 2012 can be found in this all-new collection by the editors of Cooking Light. This volume is filled with more than 700 recipes to bring new dishes and flavor combinations to your table, as well as fresh takes on all-time favorites. More than 70 full-color photographs, fresh ingredients, quick tips, the latest cooking techniques, and information about innovative kitchen equipment make this your must-have resource for preparing healthy and flavorful food. More than 100 menus are included to help you plan for every occasion. From everyday dinners to weekend entertaining, Cooking Light helps you round out your favorite dishes with excellent recipe-pairing suggestions."
R: Recipes for Analysis, Visualization and Machine Learning
Author: Viswa ViswanathanPublisher: Packt Publishing Ltd
ISBN: 178728879X
Category : Computers
Languages : en
Pages : 958
Book Description
Get savvy with R language and actualize projects aimed at analysis, visualization and machine learning About This Book Proficiently analyze data and apply machine learning techniques Generate visualizations, develop interactive visualizations and applications to understand various data exploratory functions in R Construct a predictive model by using a variety of machine learning packages Who This Book Is For This Learning Path is ideal for those who have been exposed to R, but have not used it extensively yet. It covers the basics of using R and is written for new and intermediate R users interested in learning. This Learning Path also provides in-depth insights into professional techniques for analysis, visualization, and machine learning with R – it will help you increase your R expertise, regardless of your level of experience. What You Will Learn Get data into your R environment and prepare it for analysis Perform exploratory data analyses and generate meaningful visualizations of the data Generate various plots in R using the basic R plotting techniques Create presentations and learn the basics of creating apps in R for your audience Create and inspect the transaction dataset, performing association analysis with the Apriori algorithm Visualize associations in various graph formats and find frequent itemset using the ECLAT algorithm Build, tune, and evaluate predictive models with different machine learning packages Incorporate R and Hadoop to solve machine learning problems on big data In Detail The R language is a powerful, open source, functional programming language. At its core, R is a statistical programming language that provides impressive tools to analyze data and create high-level graphics. This Learning Path is chock-full of recipes. Literally! It aims to excite you with awesome projects focused on analysis, visualization, and machine learning. We'll start off with data analysis – this will show you ways to use R to generate professional analysis reports. We'll then move on to visualizing our data – this provides you with all the guidance needed to get comfortable with data visualization with R. Finally, we'll move into the world of machine learning – this introduces you to data classification, regression, clustering, association rule mining, and dimension reduction. This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: R Data Analysis Cookbook by Viswa Viswanathan and Shanthi Viswanathan R Data Visualization Cookbook by Atmajitsinh Gohil Machine Learning with R Cookbook by Yu-Wei, Chiu (David Chiu) Style and approach This course creates a smooth learning path that will teach you how to analyze data and create stunning visualizations. The step-by-step instructions provided for each recipe in this comprehensive Learning Path will show you how to create machine learning projects with R.
Recipes and Reciprocity
Author: Hannah Tait NeufeldPublisher: Univ. of Manitoba Press
ISBN: 0887552935
Category : Social Science
Languages : en
Pages : 241
Book Description
Recipes and Reciprocity considers the ways that food and research intersect for both researchers, participants, and communities demonstrating how everyday acts around food preparation, consumption, and sharing can enable unexpected approaches to reciprocal research and fuel relationships across cultures, generations, spaces, and places. Drawing from research contexts within Canada, Cuba, India, Malawi, Nepal, Paraguay, and Japan, contributors use the sharing of food knowledge and food processes (such as drying, steaming, mixing, grinding, and churning) to examine topics like identity, community-based research ethics, food sovereignty, and nutrition. Each chapter highlights practical and experiential elements of fieldwork, incorporating storytelling, recipes, and methodological practices to offer insight into how food facilitates relationship-building and knowledge-sharing across geographical and cultural boarders. Contributors to this volume bring a range of disciplinary backgrounds—including anthropology, public health, social work, history, and rural studies—to the exploration of global and Indigenous foodways, perceptions around ethical eating and authenticity, language and food preparation, perspectives on healthy eating, and what it means to develop research relationships through food. Challenging colonial, heteropatriarchal, and methodological divisions between academic and less formal ways of knowing, Recipes and Reciprocity draws critical attention to the ways food can bridge disciplinary and lived experiences, propelling meaningful research and reciprocal relationships.
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