Price: $40.00 - $20.00
(as of Dec 17, 2024 14:36:08 UTC – Details)
NEW YORK TIMES BESTSELLER
NAMED A BEST COOKBOOK OF FALL 2023 BY FOOD & WINE, DELISH, and TASTING TABLE
Over 100 easy-to-follow recipes that teach you how to learn from your mistakes and become a better cook, from the culinary genius who created the Babish Culinary Universe YouTube channel in this long-awaited companion.
In his wildly popular Basics with Babish series, YouTube star Andrew Rea, who has amassed millions of subscribers, attempts, often fails, but always teaches cooking techniques for all levels of cooks. He’s explained everything from how to make challah bread and English muffins to Asian dumplings and homemade bacon. Now those classic, essential recipes (and many more) are compiled into an authoritative cookbook which contains hundreds of step-by-step photographs with tips and tricks to help you troubleshoot anything from broken butter to burnt bread to bony branzino. Basics with Babish isn’t just a kitchen Bible for a new generation of home chefs, it’s a proud reclamation of mistakes which encourages you to learn from your and Andrew’s missteps alike.
Andrew Rea launched Binging with Babish on YouTube in 2016, recreating and reimagining dishes from famous television programs and movies inspired by everything from Mad Men to The Simpsons to Game of Thrones. The tie-in cookbook, Binging with Babish, was an instant New York Times bestseller, and fans of that book and countless more will delight in this new cookbook which will truly teach you how to cook, with Rea’s beloved sense of humor and guiding hand throughout.
From the Publisher
Publisher : S&S/Simon Element (October 24, 2023)
Language : English
Hardcover : 464 pages
ISBN-10 : 198216753X
ISBN-13 : 978-1982167530
Item Weight : 3.65 pounds
Dimensions : 8 x 1.3 x 10 inches
Customers say
Customers find the recipes in the book delicious and good. They appreciate the tips, information, and humor in the book. Readers find cooking interesting and fun, with the videos being enjoyable.
AI-generated from the text of customer reviews
