Machine Learning Crash Course for Engineers

Machine Learning Crash Course for Engineers is a beginner-friendly guide to machine learning algorithms and techniques, with Python programming examples and step-by-step demonstrations to solve real-world problems.

Format: Hardback
Length: 453 pages
Publication date: 03 January 2024
Publisher: Springer International Publishing AG

Machine Learning Crash Course for Engineers is a comprehensive and accessible introductory guide to machine learning algorithms and techniques designed for students, engineers, and busy technical professionals. The book delves into the practical applications of machine learning, systematically progressing from foundational concepts to advanced topics, covering both theory and real-world applications. With extensive illustrations and step-by-step demonstrations, readers are empowered to implement machine learning models to solve practical problems. Whether you are a novice seeking to grasp the fundamentals of machine learning or a seasoned professional looking to expand your expertise, this powerful tutorial serves as an invaluable resource for quickly acquiring a solid foundational understanding of this rapidly evolving field.

The book begins by introducing the fundamental concepts of machine learning, including supervised and unsupervised learning, regression and classification, and neural networks. It then explores various machine learning algorithms, such as linear regression, logistic regression, decision trees, random forests, and support vector machines, explaining their workings and how they can be applied to solve different types of problems.

Throughout the course, real-world examples and case studies are used to illustrate the practical applications of machine learning. These examples range from healthcare and finance to image recognition and natural language processing, showcasing the versatility and impact of machine learning in various industries.

In addition to the theoretical explanations, the book provides detailed Python programming examples that help readers implement machine learning models and solve practical problems. Each programming example is accompanied by clear explanations, code snippets, and screenshots, making it easy for readers to follow along and apply the learned concepts to their own projects.

Furthermore, the book includes a comprehensive glossary of machine learning terms and concepts, as well as a list of further resources for those who wish to delve deeper into the field. This includes online courses, tutorials, and research papers, providing a valuable roadmap for those who want to advance their knowledge and skills in machine learning.

In conclusion, Machine Learning Crash Course for Engineers is a must-read for anyone interested in gaining a deep understanding of machine learning algorithms and techniques. Whether you are a student, engineer, or professional seeking to expand your knowledge in this rapidly evolving field, this book offers a comprehensive and practical guide that will help you achieve your goals.

Weight: 875g
Dimension: 235 x 155 (mm)
ISBN-13: 9783031469893
Edition number: 1st ed. 2024