SKU: 12992904712

Cake Picnic (Elisa Sunga)

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Description

Cake Picnic (Elisa Sunga)From the founder of Cake Picnica series of joyful, diverse, and deliciously indulgent gatherings where every attendee brings a whole cakethis cookbook of 50 baking recipes includes a guide to hosting your own confectionery events and encourages bakers to lean into play, connection, communityand lots of cake! It all started with a dream: A few friends lounging in the park on a sunny day, eating cake. Elisa Sunga posted the invitation to that first ever

From the founder of Cake Picnic—a series of joyful, diverse, and deliciously indulgent gatherings where every attendee brings a whole cake—this cookbook of 50 baking recipes includes a guide to hosting your own confectionery events and encourages bakers to lean into play, connection, community—and lots of cake!

It all started with a dream: A few friends lounging in the park on a sunny day, eating cake. Elisa Sunga posted the invitation to that first-ever cake picnic and, to her surprise and delight, nearly 200 people showed up. And so, Cake Picnic, a joy-filled gathering where each attendee brings a whole cake to share with friends old and new, was born. Its immense, immediate popularity inspired Elisa to take her picnic series on the road, traveling from LA to New York and beyond. When she realized she couldn’t bring Cake Picnic to everyone, everywhere in the world, she did the next best thing: She wrote this book.
 
Part how-to guide, part recipe collection, Cake Picnic provides everything you need to host your own delightfully decadent cake picnic. Here is practical advice for planning, hosting, and attending: how to choose a theme, prepare your guests, set up the event, encourage connection, transport whole cakes, and more. But the icing on the—you guessed it—cake is the 50 recipes within. 

Organized by theme, from an Autumn Harvest Cake Picnic to an Afternoon Tea Cake Picnic, a Beach Cake Picnic to a Salty-Sweet Cake Picnic, these imaginative recipes will inspire your creativity and tempt your sweet tooth:

  • Sour Cherry & Pistachio Buttermilk Cake
  • Torched Rosemary Caramel Cake
  • Chocolate & Earl Grey Whipped Cream Cake
  • Guava Cream Cheese Bundt Cake
  • Roasted Apple & Sesame Upside-Down Cake
  • Pretzel S’mores Cake
  • And many more!


Let this book be your invitation to spread joy through baking and plan your own festive celebration. And never apologize for trying ten slices in one sitting—happiness often comes frosted, sprinkled, and cut into generous servings.

THE CAKE PICNIC PHENOMENON: What started as a sweet idea for a picnic with friends snowballed into a movement. The very first cake picnic had nearly 200 guests, just through word of mouth. The series has since expanded to San Francisco, San Diego, New York, London, and beyond. The multi-thousand-person waitlist is proof that everyone wants to partake in a cake picnic, and now this book makes that possible!

HOST YOUR OWN: This beautiful book encompasses both a tantalizing recipe collection and a guide to planning and hosting so anyone can put on a cake picnic. Picnic themes include Confetti, New Year, Floral, Chocolate Everything, and plenty of encouragement to come up with your own!

CREATIVE RECIPES: Recipes include lots of layer cakes with frostings, soaks, and beautiful decoration; interesting flavor combinations, such as lemon saltine, rose geranium, chocolate and star anise; and a range of cake types, including loaf cakes, dome cakes, trifles, and more.

GREAT GIFT: Beautiful photos and tons of inspiration for pretty cake toppings and floral decorations make this gorgeous book the perfect gift for bakers, food lovers, and aspirational picnickers.

Perfect for:

  • Cake lovers
  • Home bakers of all levels
  • Anyone who dabbles in baking or enjoys crafty projects
  • Fans of Cake Picnic and picnics in general
  • Fans of Cherry Bombe, Christina Tosi, Broma Bakery, or Natasha Pickowicz
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SKU: 12992904712

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4.2 ★★★★★
Based on 19 reviews
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Par
Chelsea, US
★★★★★ 5
Excellent book on ML
Format: Paperback
This is a great book on machine learning. Topics covered are extensive - from beginner level to advanced topics including math behind different algorithms. However, not "all" algorithms are covered. Please go through the table of contents. The first part - 11 chapters - covers machine learning concepts and second part covers advanced topics with Pytorch. There are lots of excellent code and they work!! The quality of the book I received is excellent. I have gone through all 742 pages, and it has held up very well!! I used Jupyter notebook to run all examples. I created a new notebook and copied and pasted the code and ran them. This approach worked very well for me. At the same time, I could experiment with my take on the code snippets and definitely added to my knowledge. Only issue I have is on the second part of the book discussing PyTorch: (1) Some packages are a bit older version: e.g., transformer 4.9.1 whereas current version is 4.48+. It took some tweaking/recoding to get the examples working. (2) There is not much discussion on why certain architecture was chosen - e.g., number of layers, is there a rule of thumb on how to improve performance by changing these parameters? Even with CUDA the code run for a long time. Therefore, experimenting with different values of parameters become too time consuming. (3) On the same note, if I can achieve test accuracy of 90%+ using logistic regression and almost the same (perhaps one or two percent better with PyTorch with IMDB movie review dataset and that two much faster why should I use PyTorch for this dataset? Obviously, PyTorch is for certain types of problems. Discussions can be included by not adding to the exhaustive (and apt) contents. Personally I was disappointed by lack of any example on time series. Must have for ML practitioner as a reference and guide.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on December 20, 2024
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Verified Purchase
Richard Hackathorn
Alexandria, US
★★★★★ 5
Excellent Textbook for Hands-On Learning of ML
Format: Kindle
This textbook is for the serious life-long learners of machine learning. There are at least two ways to ‘consume’ this book. For the expert in ML, this is a textbook to study as a clear comprehensive ML overview and then to dive into sections of interest or ignorance. The concepts are grounded in code examples and are well cited (with links) to sources. Further, this textbook is appropriate if you are TensorFlow-centric and want to broaden into cutting-edge ML models/tools coded in PyTorch. For a new learner to ML, this is a textbook to DO (not just READ) with hands-on and brain-engaged. If you realize that ML is a key life-long skill for your career, consider this textbook as part of a daily learning habit (10-30 min). From personal experience, my advice to the new learner is as follows… First, clone the GitHub repository, setup your Python environment, and study the textbook, while working through the notebooks. Go on tangents and break the code. Do this methodically as part of your daily learning habit, but do not hesitate to jump ahead several chapters to prepare for tomorrow’s meeting. There is enough excellent material here for a full year of ML adventures. I did a similar strategy with Raschka’s first textbook. About four years ago, I had finished Andrew Ng’s Deep Learning Specialization as a student in his first cohort. I knew the concepts well but could not do the actual application coding. I was surprised how my Python coding improved by following Raschka’s clean and elegant style. And Raschka’s code examples were meaty enough to be springboards into working applications. Several textbook editions later, what is different about this new edition? First, it moves you through scikit-Learn (a firm foundation) to PyTorch, instead of TensorFlow. PyTorch is a better stepping-stone, both conceptually and practically. With PyTorch, you will go further with less energy, while being able to convert your efforts into TensorFlow as needed. In addition, most of the cutting-edge ML/AI/DL research is in PyTorch. It is nice to read a recent arXiv paper, clone their repository, click on the Colab tutorial, and replicate their experiments, along with picking up a ton of new coding tricks & tips. I am excited to work through these PyTorch sections to hone my skills. Second, there is a clear recognition of model tracking and tuning practices. This is often a gap in other ML textbooks and courses. Once you progress beyond the simple demo examples in a lecture, you realize that the real work is experiments, more experiments, and still more experiments, so that you must understand what the model architecture and hyperparameters are doing to your dataset. There is good coverage of scikit-Learn pipeline, grid search, model performance, and the like. Third, ML/AI/DL practice is rapidly evolving. Every week new ML packages/services become available that could save much grief on your current project. What is refreshing about Raschka’s textbook series is that he constantly adding cutting-edge topics because he likes to stay current and to help us stay current. Hence, this edition contains recent ML treats as: transformers, self-supervised learning, autoencoders-to-GAN, graph neural networks, DBSCAN, t-SNE (with brief mention of UMAP), and PyTorch-Lightning.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on February 26, 2022
A
Verified Purchase
Amazon Customer
Houston, US
★★★★★ 4
Just learning it
Format: Paperback
Nice learning book just have to finish it
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on December 10, 2025
K
Verified Purchase
Kindle Customer
West Palm Beach, US
★★★★★ 5
Very useful book
Format: Paperback
I use it for the machine learning class I teach.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 3, 2026
T
Verified Purchase
Tommy Jonsson
Cuba, US
★★★★★ 5
Cover many areas in detail and recommendations for more to read for what's outside
Format: Paperback
Good book!
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 4, 2026

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