Machine Learning For Vehicle Control – alle Bücher und CDs, Seite 3

Benjamin Tan Wei Hao, Shanoop Padmanabhan, Varun Mallya
Build a Machine Learning Platform (from Scratch)

Get your machine learning models out of the lab and into production!Delivering a successful machine learning project is hard. Build a Machine Learning Platform (From Scratch) makes it easier. In it, you'l…

lieferbar ab 25.11.2025.

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Computational Intelligence for Machine Learning and Healthcare Informatics

This book presents a variety of techniques designed to enhance and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics. It is intended to provide a uniqu…

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Prashad
Optimization Algorithms for Machine Learning: Theory and Practice

In the realm of machine learning, optimization algorithms play a pivotal role in refining models for optimal performance. These algorithms, ranging from classic gradient descent to advanced techniques lik…

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Machine Learning Methods for Multi-Omics Data Integration

Chapter 1: Introduction to Multiomics Technology, Ahmed Hajyasien.- Chapter 2: Multi-omics Data Integration Applications and Structures, Ammar El-Hassa.- Chapter 3: Machine learning approaches for multi-o…

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Ricky Leung
Leveraging GenAI for Machine Learning Education in Public Health

This book explores how ChatGPT, as a generative AI (Gen-AI) platform, can support education, research, and skill development in artificial intelligence (AI) and machine learning (ML) for public health app…

lieferbar ab 31.12.2025.

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Andreas Tilevik
Multivariate Statistics and Machine Learning in R For Beginners

This book is more than just a book -- it is a full course designed as an interactive guide for beginners in multivariate analysis. Combining theoretical videos with practical examples in R, it offers read…

lieferbar ab 8.11.2025.

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Anupam Bagchi, Pramod Gupta
Essentials of Python for Artificial Intelligence and Machine Learning

This book introduces the essentials of Python for the emerging fields of Machine Learning (ML) and Artificial Intelligence (AI). The authors explore the use of Python's advanced module features and apply …

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Harnessing AI, Machine Learning, and IoT for Intelligent Business

This book addresses the growing need for understanding the practical implications of these technologies in the context of financial management. The convergence of AI, ML, and IoT has revolutionized variou…

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Harnessing AI, Machine Learning, and IoT for Intelligent Business

This book is a comprehensive guide that explores the integration of artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT) in the realm of business management and finance. T…

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2 Bücher

Machine Learning Models and Architectures for Biomedical Signal Processing

Machine Learning Models and Architectures for Biomedical Signal Processing presents the fundamental concepts of machine learning techniques for bioinformatics in an interactive way. The book investigates …

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Uncertainty for Safe Utilization of Machine Learning in Medical Imaging

Lecture Notes in Computer Science - Band 16166

This book constitutes the refereed proceedings of the 7th Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, UNSURE 2025, held in conjunction with MICCAI 2025, in Daejon,…

lieferbar in mind. 4 Wochen

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Samuel Ackerman, Guy Barash, Onn Shehory, Orna Raz
Theory and Practice of Quality Assurance for Machine Learning Systems

This book is a self-contained introduction to engineering and testing machine learning (ML) systems. It systematically discusses and teaches the art of crafting and developing software systems that includ…

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Wesley Pacheco Calixto, Marcio Rodrigues Cunha Reis, Lucas Diniz Silva Morais, Wanderson Rainer Hilário Araújo
Control and Tracking Techniques for Switched Reluctance Machines

Control and Tracking Techniques for Switched Reluctance Machinesprovides detailed and practical instructions for implementing drive and control techniques for switched reluctance machines (SRMs), which ca…

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Statistical Modeling and Simulation for Experimental Design and Machine Learning Applications

This volume presents a selection of articles on statistical modeling and simulation, with a focus on different aspects of statistical estimation and testing problems, the design of experiments, reliabilit…

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Proceedings of the International Conference on Machine Learning, Deep Learning and Computational Intelligence for Wireless Communication

This book is a collection of best selected research papers presented at the 2nd Conference on Machine Learning, Deep Learning and Computational Intelligence for Wireless Communication (MDCWC 2023) held du…

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Bosen Lian, Wenqian Xue, Bahare Kiumarsi, Hamidreza Modares
Integral and Inverse Reinforcement Learning for Optimal Control Systems and Games

Integral and Inverse Reinforcement Learning for Optimal Control Systems and Games develops its specific learning techniques, motivated by application to autonomous driving and microgrid systems, with brea…

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Recent Advances in Machine Learning Techniques and Sensor Applications for Human Emotion, Activity Recognition and Support

This book explores integrating machine learning techniques and sensor applications for human emotion and activity recognition, creating personalized and effective support systems. It covers state-of-the-a…

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Yannick Lingelbach
Application of Data Mining and Machine Learning Methods to Industrial Heat Treatment Processes for Hardness Prediction

This work presents a data mining framework applied to industrial heattreatment (bainitization and case hardening) aiming to optimize processes and reduce costs. The framework analyses factors such as mate…

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Steven L. Brunton, J. Nathan Kutz
Data-Driven Science and Engineering

Data-driven discovery is revolutionizing how we model, predict, and control complex systems. Now with Python and MATLAB®, this textbook trains mathematical scientists and engineers for the next generation…

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Shallow Learning vs. Deep Learning

This book explores the ongoing debate between shallow and deep learning in the field of machine learning. It provides a comprehensive survey of machine learning methods, from shallow learning to deep lear…

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