Machine Learning for Engineering & Science Applications | IIT Madras - #104 Application | Part 3 | Solution | Machine Learning for Engineering & Science Applications

Welcome to 'Machine Learning for Engineering & Science Applications' course ! Building upon the previous lecture, we'll now explore a practical solution to the topology optimization problem using CNNs. We'll leverage the powerful "99 line code" by Sigmund, a widely used method for generating optimized structures. The lecture will guide you through the process of defining the input (the initial shape) and output (the optimized shape), utilizing the familiar encoder-decoder architecture, and choosing an appropriate loss function. You'll see how CNNs can effectively predict the optimal distribution of material within a structure, satisfying given constraints. NPTEL Courses permit certifications that can be used for Course Credits in Indian Universities as per the UGC and AICTE notifications. To understand various certification options for this course, please visit https://nptel.ac.in/courses/106106198 #TopologyOptimization #CNN #EncoderDecoder #LossFunction #99LineCode #SegmentationTask