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

4.5 ★★★★★
Based on 2346 reviews
Sort
Highest Rating
Newest First
Oldest First
Product Reviews
M
Verified Purchase
Michelle
Boise, US
★★★★★ 5
Keeps him
Size: 4 Inch (Pack of 2)
My dog is obsessed with these. Favorite toy
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 21, 2026
G
Verified Purchase
Gayla
Birmingham, US
★★★★★ 5
My picky yorkies love these
Size: 4 Inch (Pack of 2)
My small dogs took to this chew. My yorkies are constantly carrying these around, even through the doggie door. They love them.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on April 26, 2026
A
Verified Purchase
Amazon Customer
Lexington, US
★★★★★ 5
Satisfied customer
Size: 4 Inch (Pack of 2)
My dog absolutely loves this. He chews on it daily. It really keeps him occupied for for a good while. I highly recommend.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on March 26, 2026
R
Verified Purchase
review58
Omaha, US
★★★★★ 4
God but..
Size: 4 Inch (Pack of 2)
My small dog loves these. None of the bones are as tough as they say. I have to change out about once a month. It gets a little pricey but they can swallow the pieces once chewed a bit.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on March 21, 2026
N
Verified Purchase
NurseUrsy
San Leandro, US
★★★★★ 5
Excellent tug toy!
Size: Large Triple, Size: Large Triple
My dog had this set of 3 interlocking rings for 7 years and they finally broke. I was so happy to be able to get a replacement set that is just as durable as the original! Just ask our Gretzky to, “get your rings” and she knows exactly what to find. She can tug these for an hour and not lose interest. She loves them. They are the perfect size for her to grab comfortably and for her human playmate to hold onto the other ring in opposition. Gretzky is half Boxer, about 85lbs and all muscle. For her first set to withstand years of tugging without breaking was surprising but they’re made well and as long as you don’t allow your dog to just sit and chew them, they’ll give you years of tugging playtime!
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on June 7, 2026

recommand products