It is our great pleasure to announce the call for manuscripts for the Journal of Big Data Theory and Practice (JBDTP) special issue - Enabling Technologies in Intelligent Healthcare: From the Internet of Things (IoT), To Artificial Intelligence, Big Data, and Blockchain.
Students from NJBDA member institutions are eligible for Rutgers MBS - NJBDA joint externship exchange program.
The New Jersey Big Data Alliance (NJBDA) has taken an important step in catalyzing research collaborations in big data, artificial intelligence, and machine learning for both researchers and practitioners with the inaugural release of its new journal.
The theme for the 9th Annual Symposium is "Building the Workforce Pipeline for a Data-Driven Economy" and will include keynotes, a panel discussion, and workshops. This year’s symposium will be held in person at the New Jersey Institute of Technology.
New Jersey Big Data Alliance Workshop Series in collaboration with Montclair State University’s New Jersey Policy Think Tank for the Food Industry and Restaurants
Data Visualization with Python Jupyter Notebooks – A Hands-on Introduction. 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.
It is our great pleasure to announce the call for papers for the Journal of Big Data: Theory and Practice (JBDTP). JBDTP is an open access peer-reviewed journal which is devoted to the publication of high-quality papers on the theoretical and practical aspects of big data, AI, applications and machine learning. Authors are invited to submit novel, high quality work that has neither appeared in nor is under consideration for publication elsewhere.
Collaborating partners TechUnited, Edge, the New Jersey Economic Development Authority (NJEDA), and the New Jersey Big Data Alliance (NJBDA), are pleased to announce the availability of the State of The State of Innovation in New Jersey Report.
This workshop focuses on learning the basics of Deep Learning with Python and Keras including data preparation, Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Recurrent Neural Networks (RNN).
The recording from the Machine Learning with Python Data Science [...]