Practical Machine Learning: A Beginner's Guide with Ethical Insights
Boca Raton: CRC Press; Chapman & Hall (2025), xii, 214 pp.
"The book provides an accessible, comprehensive introduction for beginners to machine learning, equipping them with the fundamental skills and techniques essential for this field. It enables beginners to construct practical, real-world solutions powered by machine learning across diverse application domains. It demonstrates the fundamental techniques involved in data collection, integration, cleansing, transformation, development, and deployment of machine learning models. This book emphasizes the importance of integrating responsible and explainable AI into machine learning models, ensuring these principles are prioritized rather than treated as an afterthought. To support learning, this book also offers information on accessing additional machine learning resources such as datasets, libraries, pre-trained models, and tools for tracking machine learning models." (Publisher description)
1 Fundamentals of machine learning, 1
2 Mathematics for machine learning, 18
3 Data preparation, 76
4 Machine learning operations, 95
5 Machine learning software and hardware requirements, 110
6 Responsible AI and explainable AI, 138
7 Artificial general intelligence, 152
8 Machine learning step-by-step practical examples, 162
Appendix: Machine learning resources, 207
2 Mathematics for machine learning, 18
3 Data preparation, 76
4 Machine learning operations, 95
5 Machine learning software and hardware requirements, 110
6 Responsible AI and explainable AI, 138
7 Artificial general intelligence, 152
8 Machine learning step-by-step practical examples, 162
Appendix: Machine learning resources, 207