A quick search led me to this set of product details from Amazon in 2014.
The description mentions:
The dataset covers products from 6 main categories, Automotive, Books, Electronics, Movies, Phones and Home including 1529 sub-categories. All products are listed over 334 independent attributes & the size 2000K of value space.
Some of the attributes might be a little useless for a machine learning model, but other may help you do things quite nicely, like clustering.
Here is an actual example from the dataset for a DSLR camera:
ITEM 1604
Binding=Electronics
Brand=Case Logic
Color=Black
EAN=0085854223799
EANList=0085854223799
Feature=Compatible with DSLR camera with attached lens
Feature=Fitted Day Holster provides bump and scratch protection
Feature=Holster tether attaches to the camera's strap so you never set the case down to take a shot
Feature=Internal dedicated lens cap slip pocket, so your lens cap is never misplaced
Feature=Holds Cameras up to 5.9 x 4 x 6 x 7.5"
ItemDimensions=46059024750
Label=Case Logic
ListPrice=2999USD$29.99
Manufacturer=Case Logic
Model=SHC-101-BK
MPN=SHC-101-BK
PackageDimensions=27694526787
PackageQuantity=4
PartNumber=SHC-101-BK
ProductGroup=Photography
ProductTypeName=CAMERA_BAGS_AND_CASES
Publisher=Case Logic
SKU=12360967Pixmania14388
Studio=Case Logic
Title=Case Logic SHC-101-BK DSLR Day Holster, Small, Black
UPC=085854223799
UPCList=085854223799