📅 2025-06-24 — Session: Completed Conceptual Mapping for Machine Learning
🕒 16:25–16:35
🏷️ Labels: Conceptual Mapping, Machine Learning, Model Evaluation, Alpaydin, Müller & Guido
📂 Project: Teaching
⭐ Priority: MEDIUM
Session Goal
The session aimed to complete the conceptual mapping of Alpaydin’s work and initiate a new conceptual map based on a different book by Müller and Guido, focusing on machine learning frameworks and model evaluation techniques.
Key Activities
- Finalized the conceptual mapping of Alpaydin’s work, establishing a system to maintain traceability by author.
- Initiated a new conceptual map for machine learning, focusing on statistical and probabilistic approaches.
- Developed an initial structure for the new conceptual map, covering topics such as statistical inference, generative and probabilistic modeling, and various learning types.
- Processed and reflected on the first three fragments of Müller and Guido’s book, focusing on introduction to learning, probabilistic approaches, and cross-validation evaluation.
- Synthesized key concepts on model evaluation and adjustment, including validation methods like cross-validation and its application in Scikit-learn.
- Detailed thematic sections on model evaluation and improvement based on Müller and Guido’s work, organizing content on evaluation, cross-validation, and improvement processes.
- Summarized thematic insights from fragments 1 to 4 of Müller and Guido’s book, covering validation techniques, hyperparameter search, and advanced evaluation in supervised models.
- Detailed a refined thematic scheme on model evaluation, including sections on cross-validation, evaluation metrics, and hyperparameter search.
Achievements
- Successfully completed the conceptual mapping of Alpaydin’s work.
- Established a solid foundation for the new conceptual map based on Müller and Guido’s book.
- Clarified and organized key concepts and methods in machine learning model evaluation.
Pending Tasks
- Continue developing the conceptual map for the remaining chapters of Müller and Guido’s book.
- Further refine and expand on the thematic sections related to model evaluation and improvement.