Machine Learning For Physicists: A hands-on approach by Sadegh Raeisi Hardcover

Description: Machine Learning For Physicists by Sadegh Raeisi, Sedighe Raeisi Estimated delivery 3-12 business days Format Hardcover Condition Brand New Description This book presents ML concepts with a hands-on approach for physicists. The book aims to enable its readers to understand the approaches available to them and to equip them to be able to apply these techniques to their research problems. Publisher Description This book presents ML concepts with a hands-on approach for physicists. The goal is to both educate and enable a larger part of the community with these skills. This will lead to wider applications of modern ML techniques in physics. Accessible to physical science students, the book assumes a familiarity with statistical physics but little in the way of specialised computer science background. All chapters start with a simple introduction to the basics and the foundations, followed by some examples and then proceeds to provide concrete examples with associated codes from a GitHub repository. Many of the code examples provided can be used as is or with suitable modification by the students for their own applications.Key Features:Practical Hands-on approach: enables the reader to use machine learningIncludes code and accompanying online resourcesPractical examples for modern research and uses case studiesWritten in a language accessible by physics studentsComplete one-semester course Author Biography Sadegh Raeisi has a background in Quantum Computing and Quantum Information Science. He completed his MSc at the University of Calgary and his Ph.D. at the Institute for Quantum Computing at the University of Waterloo, as well as a Postdoc at the Max Planck Institute for the Science of Light in Erlangen. He then moved back to his home country and has held a faculty position since 2017. With about 18 years of research experience within the field of Quantum Computing, Sadegh is probably most recognized for his pioneering works on Macroscopic Quantumness and algorithmic cooling, including finding the cooling limit of Heat-bath Algorithmic Cooling (HBAC) techniques which was an open problem for a decade, and for inventing the Blind HBAC technique, which is the optimal and practical HBAC technique.Sedighe Raeisi has a background in high-energy physics, nonlinear dynamics and chaotic systems. She holds a Ph.D. from Ferdowsi University of Mashhad where she also worked for 2 years as a lecturer after graduation. Her areas of expertise include machine learning and deep learning with special focus on Natural Language Processing (NLP), Machine Vision, Graph Neural networks and time series forecasting. She is currently working as a Data scientist in the Research and Development division of Irans largest telecommunications company. Details ISBN 0750349557 ISBN-13 9780750349550 Title Machine Learning For Physicists Author Sadegh Raeisi, Sedighe Raeisi Format Hardcover Year 2023 Pages 233 Publisher Institute of Physics Publishing GE_Item_ID:157542697; About Us Grand Eagle Retail is the ideal place for all your shopping needs! With fast shipping, low prices, friendly service and over 1,000,000 in stock items - you're bound to find what you want, at a price you'll love! Shipping & Delivery Times Shipping is FREE to any address in USA. Please view eBay estimated delivery times at the top of the listing. Deliveries are made by either USPS or Courier. We are unable to deliver faster than stated. International deliveries will take 1-6 weeks. NOTE: We are unable to offer combined shipping for multiple items purchased. This is because our items are shipped from different locations. Returns If you wish to return an item, please consult our Returns Policy as below: Please contact Customer Services and request "Return Authorisation" before you send your item back to us. Unauthorised returns will not be accepted. Returns must be postmarked within 4 business days of authorisation and must be in resellable condition. Returns are shipped at the customer's risk. We cannot take responsibility for items which are lost or damaged in transit. For purchases where a shipping charge was paid, there will be no refund of the original shipping charge. Additional Questions If you have any questions please feel free to Contact Us. Categories Baby Books Electronics Fashion Games Health & Beauty Home, Garden & Pets Movies Music Sports & Outdoors Toys

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End Time: 2024-11-07T06:11:28.000Z

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