It's a collaborative event between WTM Mysore , Mathworks ,Co-learning Lounge and Applied Singularity Kindly subscribe to our Youtube channel - https://lnkd.in/e9mME-a Follow me on Twitter for event updates : https://twitter.com/URengaraju Master class: AI using MATLAB Developing and deploying ML and DL algorithms (45 mins) Youtube LIVE url : https://www.youtube.com/watch?v=bUYWrwsEVrk Complementing AI models with Physics based models for making Smarter Decisions (25 min) Speaker profiles: Dr. Shayoni Dutta is a Senior Application Engineer at MathWorks and focuses on technical computing. Her core experience lies in computational biology models and simulation, advanced statistics, machine learning, deep learning, medical imaging, and clinical-trial analytics. Prior to joining MathWorks, Shayoni worked as a data scientist at Bayer, and before that, as an imaging scientist at Sun Pharma Advanced Research Center. She also has served as adjunct faculty for the last six years at National Institute of Forensic Sciences and Criminology under Home Ministry. She has a Ph.D. in computational biology from Indian Institute of Technology, Delhi. She has published and reviewed papers in numerous international conferences and journals. Amit Doshi works as Principal Application Engineer at MathWorks, where he focuses on Engineering-AI using MATLAB. He works closely with customers in the areas of predictive maintenance, digital twin, smart manufacturing, and big data. Amit has over 13 years of experience working across industry. Prior to joining MathWorks, he worked on system simulations, test-setup development, and workflow automation at Suzlon Energy Limited in Pune and Germany, Texas Instruments in Germany, and Indian Institute of Technology-Bombay. Amit holds a bachelor’s degree in mechanical engineering and a master’s degree in mechatronics. Speaker 3 : Sharmistha Chatterjee (3 to 4 pm) Abstract : Machine learning has played an increasing important role in big data due to its capability of efficiently extracting meaningful information and adding valuable knowledge to large diverse systems. Data from multiple organizations may exhibit different privacy policy and requirements, related to sharing data publicly while processing, assimilating and training the data in scalable architectures. As data distribution and sharing gained prominence, ML research felt the need of preserving privacy in ML models so as to prevent leakage of sensitive information outside. In this context, we highlight several mechanisms to build accurate ML models without violating privacy concerns. BIO : I’m a Data Science professional with experience in the field of Machine Learning and Cloud applications. I have graduated from Aalto University. I have filed 5 US patents and published conference and journal papers. Privacy in ML Our Community Partners : Co-Learning Lounge : Applied Singularity: Applied Singularity is a platform where IoT, AI and Bio professionals can learn about the latest in frontier tech, develop usable skills, find top jobs, access key resources and build their professional networks. Download the Applied Singularity mobile app from www.appliedsingularity.com/app.
I am a certified Professional Google Cloud Architect and Google Cloud Developer Expert in Machine Learning.
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