SKU: 34017673806

CHEVROLET VOLT 2016 2017 2018 2019 17" FACTORY OEMWHEEL RIM 5724 22971549

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Description

CHEVROLET VOLT 2016 2017 2018 2019 17" FACTORY OEMWHEEL RIM 5724 22971549Item DescriptionONE CHEVROLET VOLT 2016 2017 2018 2019 17 INCH ALLOY RIM WHEEL FACTORY OEM 5724 22971549 23230397Manufacturer Part Number: 22971549 ; 23230397Hollander Number: 5724Condition: Remanufactured (aka reconditioned) to Original Factory ConditionFinish: MACHINED SILVERSize: 17" x 7"Bolts: 5x105mmOffset: 41 mmPosition: UNIVERSALNOTE: The buyer is responsible for fitment;*Center Cap(s), Valve Stem(s), Valve Stem Sensor(s),TMPS, Tire(s), Lug

Item Description

ONE CHEVROLET VOLT 2016 2017 2018 2019 17 INCH ALLOY RIM WHEEL FACTORY OEM 5724 22971549 23230397


Manufacturer Part Number: 22971549 ; 23230397
Hollander Number: 5724
Condition: Remanufactured (aka reconditioned) to Original Factory Condition
Finish: MACHINED SILVER
Size: 17" x 7"
Bolts: 5x105mm
Offset: 41 mm
Position: UNIVERSAL



NOTE: The buyer is responsible for fitment;
*Center Cap(s), Valve Stem(s), Valve Stem Sensor(s),
TMPS, Tire(s), Lug Nut(s) as well as Lug Nut Covers are NOT Included.

In case if you are looking for a set of 4 wheels for your car please let us know.

Vehicle Fitment

2016 CHEVROLET VOLT 17" FACTORY OEM WHEEL RIM,
2017 CHEVROLET VOLT 17" FACTORY OEM WHEEL RIM,
2018 CHEVROLET VOLT 17" FACTORY OEM WHEEL RIM,
2019 CHEVROLET VOLT 17" FACTORY OEM WHEEL RIM,
5 SPOKE FACTORY ORIGINAL WHEEL RIM


Quality Management

Product quality is our top concern, so i1parts solely with the highest quality remanufacturers, therefore each wheel undergoes a rigorous process of remanufacturing and various inspections based on internationally recognized standards to make sure its structure is 100% sound, straight and true, using state of the art technology and methods by the highest quality remanufacturers, many of which are ISO 9001 and SAE J2530 certified, so our customers can find replacement wheels that truly are just like new.
All of our remanufactures use computerized systems to match the factory color. To further improve the satisfaction of our customers we then inspect every wheel prior to listing making sure the color is as close to factory as possible.

Payment

Price is important factor to our customers, usually our prices are certainly competitive, but sometimes our quality control model does not always permit us to have the lowest prices. Therefore we have created a Damaged Wheel Buy Back (Recycling) program to decrease the overall cost for our customers while also offering an environmentally safe way of disposing of their old wheels. Only OEM rims are qualified for Damaged Wheel Buy Back (Recycling) program.

Items will not ship until payment is received. We are required to collect sales tax to all orders. This will be added to your order upon checkout. Please contact us for more information.

Shipping Information

All wheels or products are shipped within the contiguous 48 states using UPS Ground services. Upon confirming your payment your item will be processed and shipped, all orders are shipped with signature required shipping service. If rush shipping is needed, please contact us for a expedited shipping quote. We can add Next Day, 2nd Day, etc. to accommodate your needs. All items are shipped in reinforced cardboard boxes and packaged to ensure protection.

Shipments to buyers in Alaska, Hawaii, Guam, Puerto Rico, the U.S. Virgin Islands or outside the United States - Please contact us for a shipping quote. Outside the U.S., buyers may be subject to local taxes, and brokerage fees. Please be aware of this before bidding or purchasing. These fees are the responsibility of the buyer.

Return Policy

Returns are accepted within 30 (thirty) days of receipt and the returned items must not be installed, used, mounted or altered in anyway. Customers may return the purchased items for any reason that makes customer unsatisfied. Please be NOTED that there is a 25% restocking fee and the customer is responsible for return shipping unless the item is found to be damaged or defective. All items must be returned in the same condition in which they were received.

Feedback

We are committed to your satisfaction. We will automatically leave positive feedback for buyers within 24 hours of receiving payment. Feedback is an important asset for buyers and sellers alike, so if you are satisfied by your experience with our services we would greatly appreciate it if you could take a moment to leave us positive feedback with 5 star ratings. If you are not completely satisfied please contact us to give us the opportunity to improve your experience. Please know that your positive feedback and 5 star rating is are appreciated and vital to the growth of our company. Thank you!!!

Shipping Notes
  • Free Standard Shipping on $100+ Orders to the USA.
  • Except Preorder products are shipped in 48 hours.
  • Delivery to the USA:
  1. Standard Shipping : 3-10 business days
  • If time is of the essence, please consider selecting expedited delivery for faster service.
Exchange/Return Notes
  • We offer a 30-day return/exchange service after receiving.
  • Final sale items are not eligible for returns or exchanges.
  • To process your return/exchange, please contact us at [email protected]
  • Please click here for more details>>> Return & Exchange Policy
SKU: 34017673806

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4.7 ★★★★★
Based on 6 reviews
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Product Reviews
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Verified Purchase
Shannon
Alexandria, US
★★★★★ 5
The best DL/ML book I have ever seen!!
Format: Hardcover
Fantastic deep-learning book! The logic is very easy to follow, but the content is very thorough when it comes to explaining the theories behind it, making it perfect for beginners as well as math and CS students. The best DL/ML book I have ever seen!!
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on November 30, 2025
W
Verified Purchase
William P Ross
Phoenix, 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.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on March 15, 2017
A
Verified Purchase
Adam
Cuba, 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.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 22, 2026
A
Verified Purchase
Amazon Customer
Draper, 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!!
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on July 14, 2017
M
Verified Purchase
mackster
Louisville, 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.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 15, 2018

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