In this DataHour Anustup will explain all about Graph Neural Nets for NLP covering the following topics in detail:
The world of Graphical Architectures models including examples of cutting-edge projects that are executed in the industry (past/ongoing and futuristic )
Defining fundamental definitions of GNN and highlighting important mathematical understanding with real-life examples only, with the context of knowledge graphs
Explaining a real world projects
Learning path for GNN Models
How to kick start career in AI with opportunities
Prerequisites: Understanding of Python programming and interest in AI with good fundamental math
Who is this DataHour for?
Students & Freshers who want to build a career in the Data-tech domain.
Working professionals who want to transition to the Data-tech domain.
Data science professionals who want to accelerate their career growth
Speaker:
Anustup Mukherjee
AI Engineer at Newton School
Anustup Mukherjee is presently working as an AI Engineer at Newton School, building the next Ed Tech revolution with the power of AI.Former to this he was an Intern at Samsung, Google Tensorflow, WRI, IIT Patna & IIT Bombay. He has 10 + years of experience of working with companies of India and Silicon Valley to develop AI solutions. He has also worked with MHRD India.He is a Presidential Award winner for AI contributions towards National Building.
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