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9:30 AM - 10:00 AM Registration
10:00 AM - 10:45 AM "AI/ML for assessing the quality of doctor consultations"
By Pranjal Aswani, Data Engineer at Halodoc.
10:45 AM - 11:30 AM "Deep Transfer Learning with Real-World Case Studies" By Dipanjan Sarkar, GDE in ML.
11:30 AM - 12:15 PM “Building the data story with the power of Graph Analytics and Visualization”
By Karthic Rao, GDE in ML
12:15 PM - 12:30 PM Break/Networking
Pranjal Aswani is a Data Engineer at Halodoc where he has worked on a few of the challenging problems that we solve, ranging from developing and maintaining backend systems to assessing the quality of consultations to how to deal with data in general and so on.
He was a GSoC 18 student for CHAOSS and a mentor in 2019 for the same org. He interned with Dunzo and NII and graduated from Mumbai University in 2018.
Dipanjan (DJ) Sarkar is a Data Science Lead at Applied Materials, leading advanced analytics efforts around computer vision, natural language processing and deep learning. He is also a Google Developer Expert in Machine Learning. He has consulted and worked with several startups as well as Fortune 500 companies like Intel and Open Source organizations like Red Hat.
In this talk, let's explore the power of Graph analytics on large datasets powered by Dgraph running on Google Kubernetes Engine.
Along with it, we'll also explore the recipes for running a stateful workload on GKE or K8's in general.
Dgraph is an open-source, distributed, native GraphDB built for scale and speed.
Let's build the story from the data as we together dig in, explore and visualize the data using the intuitive graph querying and distributed graph processing capabilities of Dgraph.