SKU: 97342617372
monsters inc monsters university

monsters inc monsters university Monsters University (DVD)

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Description

monsters inc monsters university Monsters University (DVD)INCLUDES BOTH MOVIES FOR ONLY $19. 99 This set is In Stock at our warehouse in Washington, Iowa. 100% Satisfaction Guaranteed 120 Day Money Back Guarantee This Box Set is Brand New and Still Sealed This set is Region 1 and will play in the USA and Canada This set is in regular DVD format Enjoy both monsterous movies over and over again. Relive every moment from the first movie, Monsters Inc. until the last second of Monsters University (the prequel).

 INCLUDES BOTH MOVIES FOR ONLY $19.99

  • This set is In Stock at our warehouse in Washington, Iowa. 
  • 100% Satisfaction Guaranteed
  • 120 Day Money Back Guarantee
  • This Box Set is Brand New and Still Sealed
  •  This set is Region 1 and will play in the USA and Canada
  • This set is in regular DVD format

Enjoy both monsterous movies over and over again. Relive every moment from the first movie, Monsters Inc. until the last second of Monsters University (the prequel). Join Sully and Mike Wizowski as they try and "put that thing back where it came from". After releasing a toxic human into the monster world they embark on a journey to return her to her "door". Along the way they realize there is much more going on with Randal and Mr. Waternoose than what they originally thought. Monsters University is a prequel to the original movie. It follows a young Mike Wizowski as he tries to get into the scaring program at MU. He meets a stuck up James Sullivan who has all it takes to be a good scarer but has never applied himself. They must learn to work together with their team so they can all be in the scaring program. If they fail they have to leave the school. 

 

THIS ITEM IS IN STOCK AND READY TO SHIP FROM OUR WAREHOUSE IN Washington, Iowa. DON'T MISS YOUR CHANCE TO GET THIS GREAT SET!

THE PHOTO BELOW IS FROM OUR WAREHOUSE AND OF THE ACTUAL ITEM WE WILL BE SHIPPING YOU!

Closed Captions and Details

Audio Language: English, French, Spanish

Subtitles: English, French, Spanish

Format: Anamorphic Widescreen (No black bars on the top or bottom)

Region Code: Region 1 (Plays in the USA and Canada)

Disc Format: Regular DVD 

Condition: Brand New and Sealed

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SKU: 97342617372

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4.5 ★★★★★
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William P Ross
Bozeman, US
★★★★★ 5
Comprehensive Look At An Incredibly Complex Topic
Format: Hardcover
Deep Learning is an advanced book with great explanations and details. There is a heavy math focus with the book's beginning chapters detailing the necessary linear algebra and probability that one will need to understand deep learning. I liked that the author's chose to cover only the parts of these subjects which are relevant to deep learning. There are many interesting philosophical sections in the book as well. Just about when I was feeling overwhelmed with the complexity of the mathematics the authors take a step back and cover the foundations of deep learning such as borrowing concepts from human learning. There was an interesting dicussion about the early studies done on the vision of cat's and monkey's in the 1970s. The text covers the entire history of deep learning and the bibliography is hundreds of sources. It is clear this is the most comprehensive text available about deep learning. For anybody interested in this topic this book is a mandatory read. There are sections about machine learning as well, which makes sense because deep learning is a subset of machine learning. These sections focused on the machine learning concepts which are most relevant to deep learning. The book was well organized and divided into three parts which cover mathematics related to deep learning, typical deep learning techniques, and then more experiment learning techniques. Often the author's state when a technique works well or when it does not, and which types of data works best for the technique. Just a warning, the math in this book is highly complex. It requires a lot of work to go through this book, but the effort will be well rewarded.
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Reviewed in the United States on March 15, 2017
A
Verified Purchase
Adam
Los Angeles, US
★★★★★ 4
Too Dry.
Format: Hardcover
This was a required textbook for my class in college. I think it was too dry. The book titled Deep Learning: From Curiosity To Mastery is much more approachable.
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Reviewed in the United States on May 22, 2026
A
Verified Purchase
Amazon Customer
Battle Creek, US
★★★★★ 5
Comprehensive! The Bible of Deep Learning!
This book has by far surpassed my expectations! I have purchased many machine learning and deep neural network books in the past, but nothing has ever come close to this book! First of all, it is written by the fathers of Deep Learning, and is therefore an authority. Secondly, the book is broken into three parts: 1. A math overview and refresher. 2. Deep Learning applications and 3. Research in Deep Learning. I can't help but go through this book from front to back. It is a smooth read, and every sentence written is meaningful. These guys know their stuff! And after you read this book, YOU WILL ALSO know your stuff! If you feel daunted by the price, just remember, you get what you pay for! I'd say they could easily charge about $300+ for this book, but they are doing everyone a very kind favor by ONLY charging this reasonable amount. You get A LOT of bang for your buck with this purchase. I hesitated at first about buying this book because of the price, but I am soooooo happy that I did! Worth every penny! Look no further, get this book and start your Deep Learning journey!!
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Reviewed in the United States on July 14, 2017
M
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mackster
San Leandro, US
★★★★★ 1
A rushed, poorly written guide of how the "experts" can't really explain what Deep Learning is
Format: Hardcover
This book, in every sense of the word, is rushed. I think the authors wanted to establish themselves as leaders of this young-ish field, but does so by sacrificing quality. It also shows that Deep Learning theory has been there for a long time, known by another name called Neural Networks. The interesting algorithms are of MLP, Back Propagation and the classical neural networks. The optimization methods such as Adam are the ones that are new and interesting, and the only ones worthy of in this book. So, essentially, what you get from this book is use A for X, B for Y and C for Z type of dry, un-intuitive, badly written waste of paper. As for the structure of the book, it's like an example of how not to structure a book. It has some linear algebra, probability at the start (not good enough, and confuses more people and wastes paper). Goes on to prove other algorithms such as PCA (yeah, ok!). Then, talks about how this architecture works for this and that architecture. So, yeah, if you really want to try out deep learning, don't buy this book. Set up Tensorflow/pytorch/ other library, run the tutorials, find an architecture for the problem you are interested in and start tweaking that. You will have far more fun and would have saved your money. The praise that this book gets is beyond me. Did Musk even read this book? I doubt it.
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Reviewed in the United States on May 15, 2018
S
Verified Purchase
Stergios Papadimitriou
Whiting, US
★★★★★ 5
The classic textbook on Deep Learning
Format: Hardcover
Deep Learning is the promising direction towards general purpose effective artificial intelligence. There is an explosion of fruitful research in recent years and a lot of applications pursued mainly from technology giants as Google, Amazon, etc. and outstanding research institutions. The book "Deep Learning " by Ian Goodfellow, Yoshua Bengio, Aaron Gourville, is an excellent piece of work. They manage to present rather difficult things in an understandable manner. The theoretical presentation is outstanding typical of "classic" books. Also, the book stays close to the practical applicability of all the methods and discusses applications extensively. There are a lot of other useful books on deep learning that follow a more practical approach by focusing on a particular deep learning software package, but this one book is certainly much more essential since it provides the required theoretical background in order to be able to do serious work on deep learning. I consider the book as "must have" for anyone that works on deep learning either in an academic or in an industrial environment.
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Reviewed in the United States on August 25, 2018

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