SKU: 71007391751
evenflo balance wide neck bottle

evenflo balance wide neck bottle Balance + Bottles

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Description

evenflo balance wide neck bottle Balance + BottlesDeveloped with Pediatric Feeding Specialists, the Evenflo Feeding Balance + Bottle is designed to support healthy bottle feeding without interfering with your breastfeeding journey. The unique, naturally sloped nipple promotes a healthy wide latch for your baby by providing a proper resting place for their lips, helping to decrease mouth fatigue. The effective 1 piece integrated vent helps prevent colic, gas, and fussiness with no extra parts to clean

Developed with Pediatric Feeding Specialists, the Evenflo Feeding Balance + Bottle is designed to support healthy bottle feeding without interfering with your breastfeeding journey. The unique, naturally-sloped nipple promotes a healthy wide latch for your baby by providing a proper resting place for their lips, helping to decrease mouth fatigue. The effective 1-piece integrated vent helps prevent colic, gas, and fussiness with no extra parts to clean or lose. The included Slow Flow Nipple has an intentional, slower flow rate and helps prevent chugging, allowing for a calm, gulp-free feeding at baby’s pace. Balance + Bottles have printed measurement markers in both ounces and milliliters to provide an easy and accurate way to measure the volume of liquid. All Evenflo bottles and nipples are 100% free of BPA, polycarbonates, PVC and phthalates, and are also made of FDA-approved food grade material.

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  • Unique, naturally-sloped nipple promotes a healthy wide latch
  • 1-piece integrated venting helps prevent colic, gas, and fussiness
  • A slower flow rate for calm, gulp-free feeding
  • Developed with Pediatric Feeding Specialists
  • Note: Wide nipples do not fit on Standard bottles, and Standard nipples do not fit on Wide bottles

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Wide Plastic Wide Glass Standard Plastic Angled Standard Plastic
Bottle Neck Width Wide (2" base) Wide  (2" base) Standard  (1.5" base) Standard  (1.5" base)
Available Bottle Sizes 5oz, 9oz 6oz 2oz, 4oz, 9oz 5oz, 9oz
Bottle Material Plastic Glass Plastic Plastic
Nipple Shape Unique, naturally-sloped nipple promotes a healthy wide latch Unique, naturally-sloped nipple promotes a healthy wide latch Unique, naturally-sloped nipple promotes a healthy wide latch Unique, naturally-sloped nipple promotes a healthy wide latch
Nipple Material 100% soft silicone 100% soft silicone 100% soft silicone 100% soft silicone
Included Nipple Flow Slow (0-3 months) Slow (0-3 months) Slow (0-3 months) Slow (0-3 months)
Nipple Flows Sold Separately Medium (4-6 months), Fast (7+ months) Medium (4-6 months), Fast (7+ months) Medium (4-6 months), Fast (7+ months) Medium (4-6 months), Fast (7+ months)
Integrated 1-piece Venting Technology Yes, helps prevent colic, gas and fussiness Yes, helps prevent colic, gas and fussiness Yes, helps prevent colic, gas and fussiness Yes, helps prevent colic, gas and fussiness
Bottle Measurement Markers Molded Printed Molded Molded
Developed with Pediatric Feeding Specialists ✓ ✓ ✓ ✓
Recommended by 9 out of 10 parents ✓ ✓ ✓ ✓
Easy to Clean ✓ ✓ ✓ ✓
Dishwasher Safe (top rack only) ✓ ✓ ✓ ✓
BPA Free ✓ ✓ ✓ ✓
Breast Pump Compatibility With Balance + Pump Adapter With Balance + Pump Adapter With most standard neck pumps With most standard neck pumps
Country of Origin Thailand Assembled in Thailand of parts made in Thailand and China Thailand Thailand

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The Vent

Effective 1-piece integrated vent helps prevent colic, gas, and fussiness with no extra parts to clean or lose.

The Flow

The included Slow Flow Nipple has an intentional, slower flow rate for a calm, gulp-free feeding at baby’s pace. Balance + Nipples are available in the following flows: Slow, Medium* and Fast* (*sold separately).

The Shape

Naturally-sloped shape for baby’s lips to rest and maintain a healthy wide latch; nipple length designed to fit comfortably in baby’s mouth

1 Piece Anti-Colic Vent

Reduces gas and fussiness

Easy Assembly

Only 4 easy-to-clean parts

Available in 2 Sizes

Standard-Neck (1.5" base) and Wide-Neck (2" base)

Available in Glass!

Check out our Wide Glass 6oz, 3pk of Thermal-Shock Resistant bottles

Spill-Proof Cap

The top of the nipple hits the cap to help prevent leaks.

Pump Compatibility

Balance + Standard Neck bottles are compatible with all Evenflo breast pumps and most other standard neck breast pump brands. Pump directly into your Balance + Wide pump with a Balance + Wide Adapter

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---- ---- Balance + Wide Baby Bottles 5oz 1pk---- Recommended by Feeding Experts and 97% of Parents ----

Shipping Notes
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SKU: 71007391751

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4.4 ★★★★★
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Verified Purchase
William P Ross
Boise, 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
Chelsea, 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
Natrona Heights, 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
Verified Purchase
mackster
Omaha, 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
Draper, 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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