Description: Synthetic Data for Deep Learning by Necmi GÜrsakal, Sadullah Çelik, Esma Birişçi Estimated delivery 3-12 business days Format Paperback Condition Brand New Description Beginning-Intermediate user level Publisher Description Data is the indispensable fuel that drives the decision making of everything from governments, to major corporations, to sports teams. Its value is almost beyond measure. But what if that data is either unavailable or problematic to access? Thats where synthetic data comes in. This book will show you how to generate synthetic data and use it to maximum effect.Synthetic Data for Deep Learning begins by tracing the need for and development of synthetic data before delving into the role it plays in machine learning and computer vision. Youll gain insight into how synthetic data can be used to study the benefits of autonomous driving systems and to make accurate predictions about real-world data. Youll work through practical examples of synthetic data generation using Python and R, placing its purpose and methods in a real-world context. Generative Adversarial Networks (GANs) are also covered in detail, explaining how they work and their potential applications.After completing this book, youll have the knowledge necessary to generate and use synthetic data to enhance your corporate, scientific, or governmental decision making.What You Will LearnCreate synthetic tabular data with R and PythonUnderstand how synthetic data is important for artificial neural networksMaster the benefits and challenges of synthetic dataUnderstand concepts such as domain randomization and domain adaptation related to synthetic data generationWho This Book Is ForThose who want to learn about synthetic data and its applications, especially professionals working in the field of machine learning and computer vision. This book will also be useful for graduate and doctoral students interested in this subject. Author Biography Necmi GÜrsakal is a statistics professor at Mudanya University, where he transfers his experience and knowledge to his students. Before that, he worked as a faculty member at the Bursa Uludag University Econometrics Department for more than 40 years. Necmi has many published Turkish books and English and Turkish articles on data science, machine learning, artificial intelligence, social network analysis, and big data. In addition, he has served as a consultant to various business organizations.Sadullah Çelik completed his undergraduate and graduate education in mathematics and his doctorate in statistics. He has written numerous Turkish and English articles on big data, data science, machine Learning, Generative Adversarial Networks (GANs), multivariate statistics, and network science. He has authored three books: Big Data, R Applied Linear Algebra for Machine Learning and Deep Learning, and Big Data and Marketing. Sadullah is currently working as Research Assistant at Aydn Adnan Menderes University, Nazilli Department of Economics and Administrative Sciences, and Department of International Trade and Finance.Esma Biriçi is a programmer, statistician, and operations researcher with more than 15 years of experience in computer program development and five years in teaching students. She developed her programming ability while studying for her bachelor degree, and knowledge of machine learning during her master degree program. She completed her thesis about data augmentation and supervised learning. Esma transferred to Industrial Engineering and completed her doctorate program on dynamic and stochastic nonlinear programming. She studied large-scale optimization and life cycle assessment, and developed a large-scale food supply chain system application using Python. She is currently working at Bursa Uludag University, Turkey, where she transfers her knowledge to students. In this book, she is proud to be able to explain Pythons powerful structure. Details ISBN 1484285867 ISBN-13 9781484285862 Title Synthetic Data for Deep Learning Author Necmi GÜrsakal, Sadullah Çelik, Esma Birişçi Format Paperback Year 2023 Pages 220 Edition 1st Publisher APress GE_Item_ID:141076419; 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
Price: 65.99 USD
Location: Fairfield, Ohio
End Time: 2024-10-27T03:17:25.000Z
Shipping Cost: 0 USD
Product Images
Item Specifics
Restocking Fee: No
Return shipping will be paid by: Buyer
All returns accepted: Returns Accepted
Item must be returned within: 30 Days
Refund will be given as: Money Back
ISBN-13: 9781484285862
Book Title: Synthetic Data for Deep Learning
Number of Pages: Xix, 220 Pages
Language: English
Publication Name: Synthetic Data for Deep Learning : Generate Synthetic Data for Decision Making and Applications with Python and R
Publisher: Apress L. P.
Publication Year: 2023
Subject: Intelligence (Ai) & Semantics, Probability & Statistics / General, General, Programming Languages / Python
Type: Textbook
Item Weight: 16.3 Oz
Item Length: 10 in
Subject Area: Mathematics, Computers, Science
Author: Esma BirişCI, Necmi Gürsakal, Sadullah Çelik
Item Width: 7 in
Format: Trade Paperback