دانلود کتاب کاربردهای دنیای واقعی یادگیری ماشین

Machine learning (ML) has emerged as a cornerstone of modern computing, transforming how data-driven decisions are made across diverse sectors—from finance and healthcare to e-commerce, cybersecurity, and environmental monitoring. As this field continues to evolve, it enables not only intelligent automation but also deeper insights through predictive analytics, classification, pattern recognition, and natural language processing. This book brings together a curated selection of contemporary research and innovative implementations that reflect the breadth and depth of ML in real-world contexts. The chapters explore a variety of themes including facial expression recognition, explainable AI, financial forecasting, sentiment analysis, biomedical diagnostics, recommendation systems, signal processing, and sustainable inventory models. Techniques such as convolutional neural networks, differential evolution, fuzzy logic, and hybrid deep learning architectures are examined with applications that are both socially relevant and technically sophisticated. This volume is intended for students, researchers, professionals, and practitioners in the fields of computer science, data science, and AI. It aims to provide a balanced perspective—bridging theoretical foundations with practical use cases—and serves as a useful reference for exploring how machine learning can be harnessed to solve complex challenges. We are deeply grateful to the authors for their valuable contributions and to the reviewers for their constructive insights. Our sincere thanks also go to our academic institutions and publishing partners for their support throughout this endeavor. We hope that this book will inspire further research and innovation in the ever-expanding field of machine learning.