Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control

Unlock the potential of data-driven discovery with our groundbreaking book, "Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control". This comprehensive textbook is specifically designed to train mathematical scientists and engineers for the next generation of scientific breakthroughs. With a focus on integrating dynamical systems modeling and control with modern methods in applied machine learning, this book is a must-have resource for anyone looking to revolutionize how they model, predict, and control complex systems.

What sets our book apart is its unique approach to bridging the gap between traditional engineering mathematics and the cutting-edge fields of data-driven methods and applied optimization. With chapters covering topics ranging from introductory to research-level material, this book is accessible to advanced undergraduate and beginning graduate students from the engineering and physical sciences. Whether you're a seasoned professional or a curious learner, there's something for everyone in this comprehensive guide.

In the second edition of this highly acclaimed textbook, we've included brand new chapters on reinforcement learning and physics informed machine learning. These additions ensure that you stay at the forefront of the latest advancements in the field and have the knowledge to tackle the most complex challenges. Additionally, significant new sections and chapter exercises have been added to provide practical hands-on experience and reinforce your understanding.

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