Our iconic lipstick has been maxed out to give lips MORE with a silky matte finish and good-for-lips formula that looks richer, feels better and lasts longer. Get MORE COLOURwith full-coverage, pigment-rich payoff in our widest range of Artist-appoved shades. Get MORE COMFORT with a creamy blend of coconut oil, organic shea butter and organic cocoa butter that conditions and nourisheslips. Get MORE CARE with instant and eight-hour moisture. Get MORE LONGWEAR with 12 hours of non-fading, long-lasting colour that leaves lips looking visibly fuller from the very first ultra-vibrant glide. Get a MORE LUXE look with a high-shine packaging design on the outside and M·A·C-embossed bullet on the inside. And finally, get MORE RESPONSIBLE with a lipstick case featuring at least 30% PCR material. The iconic matte Lipstick that changed the world we live in may have been reimagined, but each famous and fresh hue still serves up that signature vanilla scent you already love
Pay in installments of $900.00 with
,
and
Shipping Estimate
USA
- USA
- CAN
- USA
- CAN
Ships within 48 hours · Estimated delivery Jul 23 - Jul 28
Promo Codes Available:
For Your Every Summer RSVP, with Code: SUMMER15
Description
MAC- M·A·CXIMAL SILKY MATTE LIPSTICK- WhirlSILKY MATTE FINISH, 12HR COMFORTABLE WEAR. PIGMENT RICH FULL COVERAGE COLOUR Our iconic lipstick has been maxed out to give lips MORE with a silky matte finish and good for lips formula that looks richer, feels better and lasts longer. Get MORE COLOURwith full coverage, pigment rich payoff in our widest range of Artist appoved shades. Get MORE COMFORT with a creamy blend of coconut oil, organic shea butter and organic cocoa butter that conditions and
SILKY MATTE FINISH, 12HR COMFORTABLE WEAR. PIGMENT-RICH/FULL-COVERAGE COLOUR
Shipping Notes
- Free Standard Shipping on $100+ Orders to the USA.
- Except Preorder products are shipped in 48 hours.
- Delivery to the USA:
- 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
4.8 ★★★★★
Based on 27 reviews
Sort
Product Reviews
★★★★★ 5
Before GPT can chat, it has to learn.
Format: Paperback
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
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on April 5, 2025
★★★★★ 5
Great examples and practical explanations
Format: Paperback
Excellent book. Highly recommend
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 19, 2025
★★★★★ 5
Great for intuitive understanding
Format: Paperback
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.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 4, 2024
★★★★★ 5
Taught me backpropagation
Format: Paperback
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.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on April 13, 2025
★★★★★ 5
An Easy Read
Format: Paperback
A good narrative description of how the various systems work. Good for getting a conceptual understanding. No math to speak of, and if you want it, you can refer to the references cited, or your other favorite machine learning book.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 7, 2024