Chris Albon's work on Machine Learning (ML) Terminology offers clear and practical explanations of key ML concepts and terms, making it easier to understand the field’s foundational elements, such as observations, learning algorithms, models, features, and predictions. His explanations help learners and practitioners grasp how different components come together in ML processes, from data preprocessing to model training and evaluation.
I have added a link to the PDFs containing these detailed explanations and practical solutions in my Google Drive for your reference.
Click the link
