wölfe tarp Gray Waterproof Canvas Tarps
SKU: 88976071974
wölfe tarp

wölfe tarp Gray Waterproof Canvas Tarps

Sale price$20.56 Regular price$22.84
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Ships within 48 hours · Estimated delivery Jun 29 - Jul 4

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Description

wölfe tarp Gray Waterproof Canvas TarpsHEAVY DUTY POLYESTER CANVAS 100% Waterproof Material Finished Size: 6" or 3% less than stated size Weight: 15 oz yd 20 Mil Thickness Silicon Treated Highly UV Resistant Reinforced brass grommets Grommet Spacing (all sides): 24" approx. Ripstop Fabric Tear Resistant Twice As Strong as Cotton Canvas Dry finish does not stain or have a strong chemical order Breathable These polyester tarps are great for indoor or outdoor use. For natural untreated canvas

HEAVY DUTY POLYESTER CANVAS

  • 100% Waterproof Material 
  • Finished Size: 6" or 3% less than stated size
  • Weight: 15 oz/yd² 
  • 20 Mil Thickness
  • Silicon Treated
  • Highly UV Resistant
  • Reinforced brass grommets
  • Grommet Spacing (all sides): 24" approx.
  • Ripstop Fabric Tear Resistant
  • Twice As Strong as Cotton Canvas 
  • Dry finish… does not stain or have a strong chemical order
  • Breathable

These polyester tarps are great for indoor or outdoor use. For natural/untreated canvas tarps, Click Here.

Material is 100% Waterproof, however, stitching on the sewn seams may allow small amounts of moisture to penetrate if water pools over these areas. 

These tarps ship out within 1-2 business days.

Shipping Notes
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Exchange/Return Notes
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  • Final sale items are not eligible for returns or exchanges.
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SKU: 88976071974

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One of the most comprehensive guides to AI and deep learning available. All concepts covered clearly and concisely with illustrations. Complex concepts are broken down into understandable terms. Even though ML and AI require some complex math, you won’t need it to get idea of what’s going on inside the computer’s “brain”. I use this as a reference when teaching AI concepts and preparing presentations. I highly recommend it
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Excellent book. Highly recommend
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Amazing book. Great examples and diagrams. If you're looking to get an intuitive grasp of deep learning, look no further. If you're an engineer looking to apply it, I would recommend pairing this with one of the more technical canonical texts and a programming focused book.
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I'm finding this book a great reference to supplement Syracuse IST 691 Deep Learning in Practice. In particular, its explanation of backpropagation is the clearest I have found yet, and that even includes 3 Blue 1 Brown, which always does excellent explanations.
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