Industrial Engineering

Lesson 1: Introduction to Machine Learning. Lesson 2: Understanding Data with Descriptive Statistics (Analyzing Data). Lesson 3: Understanding Data with Visualization (Analyzing Data). Lesson 4: Preprocessing Data (Preparing Data). Lesson 5: Feature Selection (Preparing Data). Lesson 6: Resampling Methods (Evaluating Algorithms). Lesson 7: Algorithm Evaluation Metrics (Evaluating Algorithms). Lesson 8: Supervised Testing of Classification Algorithms (Evaluating Algorithms). Lesson 9: Supervised Testing of Regression Algorithms (Evaluating Algorithms). Lesson 10: Model Selection (Evaluating Algorithms). Lesson 11: Pipes (Evaluating Algorithms). Lesson 12: Ensemble Methods (Improving Results). Lesson 13: Algorithm Parameter Tuning. (Improving Results) Lesson 14: Model Finalization. (Presenting Results)

This machine learning course aims to introduce students to fundamental machine learning concepts and techniques. It covers steps such as data analysis, preparation, algorithm evaluation, and results presentation. Students will gain skills in understanding data, preprocessing, feature selection, and resampling. Furthermore, the course aims to teach advanced topics such as classification, regression algorithms, ensemble methods, and parameter tuning. This course aims to equip students with a solid foundation of knowledge and skills in the field of machine learning.