BEGIN:VCALENDAR VERSION:2.0 PRODID:-//Drupal//recurring_events_ical//2.0//EN BEGIN:VEVENT UID:1bbb6419-a812-4c67-a01e-be5544aeb169@support.access-ci.org DTSTAMP:20240307T154743Z DTSTART:20240328T170000Z DTEND:20240328T190000Z SUMMARY:Developing a scalable CNN for Building Damage Classification DESCRIPTION:We are excited to announce our first webinar on “Developing a scalable CNN for building damage classification” on March 28th at 12 - 2 PM Central Time. This webinar will guide you through building and depl oying effective Convolutional Neural Networks (CNNs) for automated buildin g damage identification. We’ll cover image classification techniques, CN N fundamentals, and hands-on experience to empower you with the skills to scale your solutions. Please Register for the Webinar: https://www.chish iki-ai.org/posts/2024-webinar-cnn-building-damage/Key Topics:Understanding Image Classification and CNNs: Explore basic machine learning models, Mu lti-layer Perceptrons (MLPs), and the core components of CNNs for image an alysis.The Building Blocks of CNNs: Delve into the essential elements of CNNs, including convolutional layers, pooling, activation functions, and m ore.Training Deep Learning Models: Learn strategies for effectively train ing your models, including data augmentation and transfer learning techniq ues.Workflow for Deep Learning: Gain practical knowledge with a step-by-s tep deep learning workflow.Case Study: Natural Hazard Detection: See real -world applications of CNNs for building damage identification after natur al disasters.Hands-on Session: Get hands-on experience building and deplo ying a CNN for damage classification using PyTorch.Pre-requisites:Please r egister to have a TACC account if you don’t already have one: https://a ccounts.tacc.utexas.edu/registerBasic understanding of Python programming is recommended but not essential.Connect with us on LinkedIn  https://www .linkedin.com/company/chishikiai/  URL:https://support.access-ci.org/events/7450 END:VEVENT END:VCALENDAR