Description
Would you like to understand Machine Learning and learn how to choose the right methods for your data? Machine Learning for Beginners offers a structured learning path to help you master the fundamentals, step by step.
You will learn how to evaluate model performance, transform data, reduce dimensionality, and balance classes. You will then explore the main regression, classification, and clustering methods to understand their principles and applications.
Each chapter includes learning objectives, a concise lesson, methodological explanations, and practice exercises with detailed, annotated solutions. This approach helps you reinforce your understanding and practise at your own pace.
The book focuses on conceptual understanding and mathematical reasoning, with no programming knowledge required. It is intended for students, teachers, and anyone wishing to build a solid foundation in Machine Learning.
