Ryan G. McClarren
Machine Learning for Engineers: Using data to solve problems for physical systems
Machine Learning for Engineers: Using data to solve problems for physical systems
YOU SAVE £8.35
- Condition: Brand new
- UK Delivery times: Usually arrives within 2 - 3 working days
- UK Shipping: Fee starts at £2.39. Subject to product weight & dimension
Bulk ordering. Want 15 or more copies? Get a personalised quote and bigger discounts. Learn more about bulk orders.
Couldn't load pickup availability
- More about Machine Learning for Engineers: Using data to solve problems for physical systems
Engineers and applied scientists must harness machine learning to solve complex problems. This text teaches state-of-the-art technologies from an engineering perspective, with examples and case studies in Python and scikit-learn. It benefits undergraduate engineering students and practicing engineers.
Format: Paperback / softback
Length: 247 pages
Publication date: 22 September 2022
Publisher: Springer Nature Switzerland AG
Engineers and applied scientists must embrace the transformative power of machine learning to tackle the increasingly intricate and data-driven challenges that arise. This comprehensive text equips students and practicing engineers from traditionally "analog" disciplines, such as mechanical, aerospace, chemical, nuclear, and civil, with state-of-the-art machine learning technologies. Dr. McClarren delves into these technologies from an engineering perspective, showcasing their specific value to engineers through practical examples based on physical systems. The book progresses from basic learning models to deep neural networks, gradually enhancing readers' ability to apply modern machine learning techniques to their current work and preparing them for future, as yet unknown, problems. Instead of a black box approach, the author teaches a broad range of techniques while emphasizing the types of problems best addressed by each. Real-world examples and case studies in areas like controls, dynamics, heat transfer, and other engineering applications are implemented using Python and the popular libraries scikit-learn and tensorflow, demonstrating how readers can apply the most up-to-date methods to their own challenges. This book serves as a valuable resource for undergraduate engineering students seeking to acquire the skills required by future employers, as well as practicing engineers looking to expand and update their problem-solving toolkit.
Weight: 409g
Dimension: 235 x 155 (mm)
ISBN-13: 9783030703905
Edition number: 1st ed. 2021
This item can be found in:
UK and International shipping information
UK and International shipping information
UK Delivery and returns information:
- Delivery within 2 - 3 days when ordering in the UK.
- Shipping fee for UK customers from £2.39. Fully tracked shipping service available.
- Returns policy: Return within 30 days of receipt for full refund.
International deliveries:
Shulph Ink now ships to Australia, Belgium, Canada, France, Germany, Ireland, Italy, India, Luxembourg Saudi Arabia, Singapore, Spain, Netherlands, New Zealand, United Arab Emirates, United States of America.
- Delivery times: within 5 - 10 days for international orders.
- Shipping fee: charges vary for overseas orders. Only tracked services are available for most international orders. Some countries have untracked shipping options.
- Customs charges: If ordering to addresses outside the United Kingdom, you may or may not incur additional customs and duties fees during local delivery.
