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ApL405

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ApL405
Machine Learning in Mechanics
Credits 3
Structure 2-0-2
Pre-requisites
Overlaps ELL784, COL341, COL774

ApL405 : Machine Learning in Mechanics

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Introduction: Linear Algebra, Probability review, Programming Basics, Challenges in Data Handling Regression: Simple Linear Regression, Multiple Linear Regression, Nonlinear Regression, Logistic regression Introduction to Machine learning: Supervised Learning, Unsupervised Learning, Classification and Clustering Algorithms Applications of Machine Learning in Mechanics: Case Studies include Identifying faulty/healthy wind turbines, Turbulent Flow Analysis, Courses of Study 2024-2025 Applied Mechanics114Leakage Detection in Hydraulic Circuits, Fault Detection in Motor- Bearings, Human Activity Recognition, Heart Sound Classification etc. Deep learning: Introduction to Neural Networks, Convolution and Artificial Neural Networks, Applications in Engineering Mechanics Practical's: MATLAB tools including Curve Fitting Toolbox, Classification Learner App, Deep Network Designer App, Tensor Flow, Training models on GPUs.