📅 2025-06-24 — Session: Developed Conceptual Maps for Machine Learning
🕒 16:15–16:25
🏷️ Labels: Machine Learning, Conceptual Maps, Alpaydin, Supervised Learning, Model Evaluation
📂 Project: Teaching
⭐ Priority: MEDIUM
Session Goal
The goal of this session was to develop and organize conceptual maps for understanding various aspects of machine learning, using insights from key texts.
Key Activities
- Established a procedure for extracting and classifying book fragments related to machine learning, focusing on their pedagogical value.
- Created a thematic map for the book ‘Introduction to Machine Learning’ by Ethem Alpaydin, summarizing key concepts such as supervised learning and model evaluation.
- Reviewed ‘Introduction to Machine Learning with Python’, highlighting practical examples and key concepts in supervised learning and feature engineering.
- Organized fragments from Alpaydin’s book to create a thematic conceptual map.
- Developed an initial conceptual scheme of machine learning, detailing foundational concepts and hierarchical organization.
- Updated the conceptual map to include decision trees, discussing their fundamentals, construction, and applications.
Achievements
- Successfully developed and organized comprehensive conceptual maps for machine learning, integrating insights from multiple sources.
Pending Tasks
- Further refinement and expansion of the conceptual maps to include more advanced topics and recent developments in machine learning.