Hands-On Quantum Machine Learning with Python, Volume -2 (Full Colour Edition)
SKU: 10734340106

Hands-On Quantum Machine Learning with Python, Volume -2 (Full Colour Edition)

Sale price$901.12 Regular price$1001.25
Save 10%

Shipping Estimate
USA
  • USA
  • CAN

Ships within 48 hours · Estimated delivery Jul 7 - Jul 12

Promo Codes Available:

For Your Every Summer RSVP, with Code: SUMMER15

Description

Hands-On Quantum Machine Learning with Python, Volume -2 (Full Colour Edition)This book is specifically designed to empower developers, practitioners, and students like you to become proficient experts in the burgeoning field of quantum machine learning. Inside this book, you'll discover:"Highly practical walkthroughs that provide concrete solutions to real world combinatorial optimization problems and challenges, equipping you with immediately applicable skills."Hands on tutorials, enriched with extensive code examples,

This book is specifically designed to empower developers, practitioners, and students like you to become proficient experts in the burgeoning field of quantum machine learning.Inside this book, you'll discover:"Highly practical walkthroughs that provide concrete solutions to real-world combinatorial optimization problems and challenges, equipping you with immediately applicable skills."Hands-on tutorials, enriched with extensive code examples, guiding you through the Variational Quantum Eigensolver (VQE), detailing its implementation, and demonstrating its practical usage for quantum machine learning."An accessible and supportive teaching style that demystifies the underlying mathematics and physics, enabling you to confidently master quantum machine learning concepts and techniques.Within this volume, you will acquire the knowledge and skills necessary to address contemporary optimization problems using real quantum computers. We will conduct an in-depth exploration of the Variational Quantum Eigensolver (VQE) and apply it to solve complex combinatorial optimization challenges.Combinatorial optimization plays a critical role across numerous industries. A prime example is the Traveling Salesman Problem (TSP), which seeks the most efficient route between multiple destinations. This is vital for parcel delivery services, aviation logistics, and virtually all aspects of the mobility sector. The book even touches on how quantum machine learning and effective trading strategies could intersect in the future. mastering these problem-solving techniques, you will be well-positioned to secure or advance your career in various fields that are being transformed the emergence of quantum computing. Learn from experienced trader insights and how they apply to the quantum realm.This book caters to students, developers, data scientists, and practitioners who are eager to apply quantum machine learning to solve tangible problems in the present day."I am new to quantum computing and machine learning altogether." - Not a problem! *Hands-On Quantum Machine Learning With Python* is precisely the resource you need. We begin with fundamental concepts, assuming no prior knowledge of either machine learning or quantum computing. You will receive comprehensive guidance throughout your learning journey. (Consider acquiring the bundle that includes "Volume 1: Getting Started").

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: 10734340106

Discover Niche Categories That Outsell

Top-Converting Item to Boost Your Average Order

4.1 ★★★★★
Based on 1144 reviews
Sort
Highest Rating
Newest First
Oldest First
Product Reviews
R
Reesy07
Bozeman, US
★★★★★ 5
Excellent Midlayer for Golf
Color: Light Brown Heather, Size: X-Large
My dad has been wearing this M MAELREG hoodie for about a week now, specifically during my early morning golf rounds where the temperature sits in the low 50s. The fit is true to size with an "athletic" cut, meaning it’s tapered enough to look sharp but has enough stretch and light enough to allow for a full shoulder turn during a golf swing. The cost is also a lot lower than some of the tech golf shirts out there. Overall this is a great shirt for golfing with an expensive look.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on January 14, 2026
A
Verified Purchase
Amazon Customer
Lowell, US
★★★★★ 4
Good not great
Color: Blue Heather, Size: XX-Large
Good hoodie. Don’t know if it’s worth the price. Would feel better if it was $10 cheaper
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on January 5, 2026
M
Meigs County Mama
Charlottesville, US
★★★★★ 5
Comfortable and casual enough for daily wear but still looks like you put thought into your look
Color: Grey Heather, Size: 3X-Large
Got this for my husband and was so pleased with the quality and fit. He wears it on top of his tee shirt and says it's one of the most comfortable hoodie he's worn. It's not too thick, but very warm. Great value as he wears it daily. Love the casual style while still looking put together.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on January 4, 2026
R
Verified Purchase
Robert S
Alexandria, US
★★★★★ 5
Highly recommend
Big fan, have purchased multiple
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on April 1, 2026
A
Verified Purchase
a tichler
New York, US
★★★★★ 4
Strechy and silky
Color: Grey Heather, Size: X-Large
Super stretchy and very silky feeling. It’s the same look at the lulu hoodie with similar material, but it’s different fabric. Very stretchy very silky
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on January 8, 2026

recommand products