Shin Yong Jun (14 results)

Paperback. Condition: new. Paperback. Are you ready to revolutionize your scientific research and engineering projects with cutting-edge AI technology?Deep Learning 101 for Scientists and Engineers is your hands-on guide to mastering deep learning without getting lost in complex math. This book is designed for scientists, engineers, and researchers eager to leverage adaptive deep learning models for real-world applications.Why This Book?Clear, Insight-Oriented Explanations: Grasp deep learning concepts through computational graphs, not dense equations.Practical, Hands-On Learning: Dive into real coding examples using PyTorch and Google Colab.Focus on Adaptive Transformers: Learn how adaptive models can dynamically adjust to real-time data in fields like biomedical engineering, autonomous systems, and industrial automation.Comprehensive Coverage: From basics like gradient descent to building advanced transformer models, everything you need is here.Who Should Read This Book?Researchers and Academics in biology, chemistry, physics, and engineering.Students eager to explore AI applications in their fields.Industry Professionals looking to enhance their systems with adaptive deep learning models.What Sets This Book Apart?Focused on adaptive deep learning models that evolve with your data.Tools and Frameworks guide for seamless implementation.Hands-on coding examples tailored to scientists and engineers. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Condition: New. SUPER FAST SHIPPING.

Condition: New. In.

Paperback. Condition: new. Paperback. Are you ready to revolutionize your scientific research and engineering projects with cutting-edge AI technology?Deep Learning 101 for Scientists and Engineers is your hands-on guide to mastering deep learning without getting lost in complex math. This book is designed for scientists, engineers, and researchers eager to leverage adaptive deep learning models for real-world applications.Why This Book?Clear, Insight-Oriented Explanations: Grasp deep learning concepts through computational graphs, not dense equations.Practical, Hands-On Learning: Dive into real coding examples using PyTorch and Google Colab.Focus on Adaptive Transformers: Learn how adaptive models can dynamically adjust to real-time data in fields like biomedical engineering, autonomous systems, and industrial automation.Comprehensive Coverage: From basics like gradient descent to building advanced transformer models, everything you need is here.Who Should Read This Book?Researchers and Academics in biology, chemistry, physics, and engineering.Students eager to explore AI applications in their fields.Industry Professionals looking to enhance their systems with adaptive deep learning models.What Sets This Book Apart?Focused on adaptive deep learning models that evolve with your data.Tools and Frameworks guide for seamless implementation.Hands-on coding examples tailored to scientists and engineers. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Condition: New. pp. 76.

First Edition. Paperbound. Illustrated. Fine in printed wrappers. A catalogue issued to accompany a retrospective of eleven films by the Korean director, Shin Sang-Ok, including My Mother and Her Guests (1961), King Yonsan (1961), Red Muffler (1964), Phantom Queen (1967,), and Eunuch (1968). With essays by various Korean film critics and an interview with Shin Sang-Ok by Kwon Yong-Min.

Condition: New. Print on Demand.

Taschenbuch. Condition: Neu. Neuware - Why This Book.

paperback. Condition: Like New. Like New. book.

Condition: Fine. Number of books: 1.

Condition: Fine. Number of books: 1.

Condition: New. Print on Demand pp. 76 23:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on White w/Gloss Lam.

Condition: New. PRINT ON DEMAND pp. 76.

Kartoniert / Broschiert. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book is a modified version of the author s thesis, EWOD-based Digital Microfluidics as a Novel Platform for Systems Biology . The author, having mastered both medicine and engineering, believes the real challenge in science and.