NJBDA Workshop Series
Knowledge Graphs in Natural Language Processing: Overcome Domain Adaptation Challenges in Language Models The event is hosted by the PISG, the MPI program and the Rutgers Urban & Civic Informatics (RUCI) Lab, the Bloustein Student Services and BGSA in collaboration with our partners at Rutgers University and our external collaborators. Event presented by Vivek Kumar, Marie Sklodowska-Curie Scholar, University of Cagliari, Italy Vivek Kumar is an NLP Enthusiast. He is presently working as a Marie Sklodowska-Curie Researcher with the University of Cagliari, Italy and Philips Research, Netherlands for PhilHumans (European Commission, Horizon 2020, ITN project). Prior to this, he worked as a Research Engineer for the project “Search for Hidden Particle” (SHiP) of the European Commission of Nuclear Research (CERN) at NUST-MiSiS. He received his MS degree from NUST-MiSiS in Computer Science. In his career so far, he has authored several publications with Journals, Book Series and [...]
NJBDA Workshop Series, in collaboration with Montclair State University's New Jersey Policy Think Tank for the Food Industry and Restaurants. Join our panel of technology and marketing experts, restaurateurs and food service professionals to discuss digital technologies, including payment tools, customer reservation, and social media marketing tools to create value and grow your profits!
The session will consist of brief presentations, with around 100 minutes of interactive work-along demo of data visualization with Jupyter Notebooks, and end with Q&A. Participants will learn to create data visualizations and can opt to either access Rutgers University’s high-performance computing (HPC) platform/cloud* or to run the code locally on their own computers.
In this workshop, after a brief overview on machine learning, we will focus on doing the hands-on training in applying ML models on various data types including image, text, and time series. We will work through the use cases of classification and regression problems and discuss where to apply supervised or unsupervised methods.
Artificial Intelligence/Machine Learning (AI/ML) methods are being used for de novo protein structure prediction. In addition to expert lectures, this crash course will provide hands-on training on AlphaFold2 and RosettaFold. These methods made a big impact in the field of protein prediction by solving a 50-year-old grant challenge.