ME-588 MACHINE LEARNING IN MECHANICAL ENGINEERING
Credit Hours = 3
COURSE CONTENT
Introduction to Artificial Intelligence (AI) and Machine Learning (ML), ML applications in mechanical systems and processes; Python for ML applications; Data Acquisition and Preprocessing, Dimensionality reduction; Supervised Learning, Regression and Classification; Model training, validation, and testing; Bias and variance, Regression Metrics, Classification Metrics, Classification algorithms (k-Nearest Neighbor, SVM, Decision Trees), Artificial Neural Networks, Deep learning architectures, Object recognition using computer vision; Unsupervised learning, k-means clustering; Reinforcement Learning in mechanical control systems, AI in Robotics; Applications of Machine Learning in performance predictions, predictive maintenance, condition monitoring, structure analysis, thermal performance analysis, quality control, and defect detection.
RECOMMENDED BOOKS
- Divya Zindani, J. Paulo Davim, Kaushik Kumar, “Artificial Intelligence in Mechanical and Industrial Engineering”, CRC Press, 2021
- Kevin P. Murph, “Probabilistic Machine Learning - An Introduction”, MIT Press, 2022.
- Christopher M. Bishop, “Pattern Recognition and Machine Learning”, Springer, 2016.
