설명
"One of the biggest hurdles in using an STL mesh model for a downward manufacturing application is the lack of geometry feature information in the STL file.
This class will demonstrate how machine learning techniques can be applied to extract geometrical information from mesh models; and explain the process of building machine learning models, feature engineering for mesh data, and parameter tuning. We will also cover Autodesk Forge integration for data translation and viewing; and demonstrate how to use AWS cloud infrastructure such as GPU computing for big data and AWS Lambda for fast online predictions."
주요 학습
- Demonstrate use of machine learning in the future of autonomous manufacturing
- Apply machine learning techniques for problems in geometry
- Integrate Autodesk Forge services in webapp
- Select appropriate AWS computing services for machine learning application
발표자
Sandip JadhavCEO and Co-Founder of CCTech, a certified Autodesk FORGE SYSTEMS INTEGRATOR partner, digital transformation enabler for AEC and manufacturing industries. CCTech is also a leading cloud platform developer such as simulationHub CFD. We are building a wide range of Autonomous CFD apps HVAC, buildings, and valve industry. We are specialized in engineering application development for our clients using BIM, Machine Learning, AI, WebApps, cloud computing technologies. We building digital twins, engineering configurators, by the convergence of REVIT IO, Inventor IO, various forge services.
Nem KumarNem Kumar is director of consulting at CCTech and has been doing product development with companies from Manufacturing, Oil & Gas and AEC domain. He has vast experience in Desktop as well as Cloud software development involving CAD, CAM, complex visualization, mathematics and geometric algorithms. He has been actively working with Autodesk Vertical and AEC product teams. His current areas of interest are Generative Modeling and Machine Learning.
Vijay MaliVijay is passionate about people and technology and working on how to bring them together to make the world a better place, a place to fulfill individual dreams. In the role of COO, his vision is to build a people-centric organization with excellent processes and systems. He is on the mission of creating an environment of freedom, collaboration, and growth for people. He wants to harness the technology to build agile and scalable systems supporting the growth of both people and organization. In his 15 years of career, Vijay has played many technical roles. He has experience in providing CFD solutions for many complex problems. He has conceptualized many software solutions, including the Pedestrian Comfort Analysis & Control Valve Performer app developed on Autodesk Forge and simulationHub. Vijay is known for his transformative way of teaching and trained more than 500 candidates on complex topics like computational fluid dynamics and design optimization. He has delivered talks at various events and engineering colleges about CFD and its use in product design optimization. Vijay holds a master's degree in aerospace engineering from the Indian Institute of Technology (IIT Bombay).
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