Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control (Brunton Steven L.)(Pevná vazba)

Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control (Brunton Steven L.)(Pevná vazba)

Data-driven discovery is revolutionizing the modelling, prediction, and control of complex systems. This textbook brings together machine learning, engineering mathematics, and mathematical physics to integrate modelling and control of dynamical systems with modern methods in data science. It

Data Mining and Machine Learning: Fundamental Concepts and Algorithms (Zaki Mohammed J.)(Pevná vazba)

The fundamental algorithms in data mining and machine learning form the basis of data science, utilizing automated methods to analyze patterns and models for all kinds of data in applications ranging from scientific discovery to business analytics. This textbook for senior undergraduate and

Machine Learning for Signal Processing: Data Science, Algorithms, and Computational Statistics (Little Max A.)(Pevná vazba)

This book describes in detail the fundamental mathematics and algorithms of machine learning (an example of artificial intelligence) and signal processing, two of the most important and exciting technologies in the modern information economy. Taking a gradual approach, it builds up concepts in a

Differential Equations, Dynamical Systems, and an Introduction to Chaos (Hirsch Morris W.)(Pevná vazba)

Hirsch, Devaney, and Smale's classic Differential Equations, Dynamical Systems, and an Introduction to Chaos has been used by professors as the primary text for undergraduate and graduate level courses covering differential equations. It provides a theoretical approach to dynamical systems and

Driving Digital Transformation Through Data and AI: A Practical Guide to Delivering Data Science and Machine Learning Products (Borek Alexander)(Paperback)

Leading digital businesses such as Netflix, Amazon and Uber use data science and machine learning at scale in all of their core business processes, but many organizations struggle to expand their projects beyond a small pilot scope. This book enables all organizations to realize the promised value

Bayesian Reasoning and Machine Learning (Barber David)(Pevná vazba)

Machine learning methods extract value from vast data sets quickly and with modest resources. They are established tools in a wide range of industrial applications, including search engines, DNA sequencing, stock market analysis, and robot locomotion, and their use is spreading rapidly. People who

Feature Engineering for Machine Learning: Principles and Techniques for Data Scientists (Zheng Alice)(Paperback)

Machine Learning Control - Taming Nonlinear Dynamics and Turbulence (Duriez Thomas)(Pevná vazba)

This is the first textbook on a generally applicable control strategy for turbulence and other complex nonlinear systems. The approach of the book employs powerful methods of machine learning for optimal nonlinear control laws. This machine learning control (MLC) is motivated and detailed in

Machine Learning and Data Science Blueprints for Finance: From Building Trading Strategies to Robo-Advisors Using Python (Tatsat Hariom)(Paperback)

Over the next few decades, machine learning and data science will transform the finance industry. With this practical book, analysts, traders, researchers, and developers will learn how to build machine learning algorithms crucial to the industry. You'll examine ML concepts and over 20 case studies

Engineering and Analyzing Multicellular Systems: Methods and Protocols (Sun Lianhong)(Pevná vazba)

Engineering Multicellular Systems: Methods and Protocols, focuses on laboratory procedures used in recent efforts for constructing synthetic multicellular systems and their applications. In particular, constructing multicellular systems to form various microbial ecosystems has been extensively

Introduction to Rocket Science and Engineering (Taylor Travis S.)(Pevná vazba)

Introduction to Rocket Science and Engineering, Second Edition, presents the history and basics of rocket science, and examines design, experimentation, testing, and applications. Exploring how rockets work, the book covers the concepts of thrust, momentum, impulse, and the rocket equation, along

The Art of Systems Architecting (Maier Mark W.)(Pevná vazba)

If engineering is the art and science of technical problem solving, systems architecting happens when you don't yet know what the problem is. The third edition of a highly respected bestseller, The Art of Systems Architecting provides in-depth coverage of the least understood part of systems

Hands-On Machine Learning with R (Boehmke Brad)(Pevná vazba)

Hands-on Machine Learning with R provides a practical and applied approach to learning and developing intuition into today's most popular machine learning methods. This book serves as a practitioner's guide to the machine learning process and is meant to help the reader learn to apply the machine

Computational Science and Engineering (Strang Gilbert)(Pevná vazba)

Encompasses the full range of computational science and engineering from modelling to solution, both analytical and numerical. It develops a framework for the equations and numerical methods of applied mathematics. Gilbert Strang has taught this material to thousands of engineers and scientists

Business Data Science: Combining Machine Learning and Economics to Optimize, Automate, and Accelerate Business Decisions (Taddy Matt)(Pevná vazba)

Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product.Use machine learning to understand your customers, frame decisions, and drive value The business analytics

Beginning Mathematica and Wolfram for Data Science: Applications in Data Analysis, Machine Learning, and Neural Networks (Villalobos Alva Jalil)(Paperback)

Enhance your data science programming and analysis with the Wolfram programming language and Mathematica, an applied mathematical tools suite. The book will introduce you to the Wolfram programming language and its syntax, as well as the structure of Mathematica and its advantages and

Human and Machine Learning: Visible, Explainable, Trustworthy and Transparent (Zhou Jianlong)(Pevná vazba)

Part I Transparency in Machine Learning.- Part II Visual Explanation of Machine Learning Process.- Part III Algorithmic Explanation of Machine Learning Models.- Part IV User Cognitive Responses in ML-Based Decision Making.- Part V Human and Evaluation of Machine Learning.- Part VI Domain Knowledge

Handbook of Thermal Science and Engineering (Kulacki Francis A.)(Pevná vazba)

Era of Artificial Intelligence, Machine Learning, and Data Science in the Pharmaceutical Industry(Paperback / softback)

The Era of Artificial Intelligence and Machine Learning in the Pharmaceutical Industry examines the drug discovery process, assessing how new technologies have improved effectiveness. Artificial intelligence and machine learning are considered the future for a wide range of disciplines and

Machine Learning in Radiation Oncology: Theory and Applications (El Naqa Issam)(Pevná vazba)

​This book provides a complete overview of the role of machine learning in radiation oncology and medical physics, covering basic theory, methods, and a variety of applications in medical physics and radiotherapy. An introductory section explains machine learning, reviews supervised and

Industrial Automated Systems: Instrumentation and Motion Control [With CDROM] (Bartelt Terry L. M.)(Pevná vazba)

INDUSTRIAL AUTOMATED SYSTEMS: INSTRUMENTATION AND MOTION CONTROL, will provide readers with state-of-the art coverage of the full spectrum of industrial maintenance and control, from servomechanisms to instrumentation. They will learn about components, circuits, instruments, control techniques,

Data Science on AWS: Implementing End-To-End, Continuous AI and Machine Learning Pipelines (Fregly Chris)(Paperback)

With this practical book, AI and machine learning practitioners will learn how to successfully build and deploy data science projects on Amazon Web Services. The Amazon AI and machine learning stack unifies data science, data engineering, and application development to help level up your skills

Fundamentals of Hydraulic Engineering Systems (Houghtalen Robert)(Pevná vazba)

Understanding Hydraulics: The Design, Analysis, and Engineering of Hydraulic Systems Fundamentals of Hydraulic Engineering Systems bridges the gap between fundamental principles and techniques applied to the design and analysis of hydraulic engineering systems. An extension of fluid mechanics,

How to Be Good at Science, Technology, and Engineering (DK)(Pevná vazba)