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Events for March 3, 2023 – June 2, 2023 – Page 8 – Office of Advanced Research Computing Events for March 3, 2023 – June 2, 2023 – Page 8 – Office of Advanced Research Computing

Python for Big Data

Register to attend the workshop at the bottom of this page. Zoom link will be emailed after filling out the registration form. Amarel account: Apply here as soon as possible. VPN setup: You have to be connected on Rutgers' network or be on VPN  to access Amarel resources. SSH setup: Windows users must install an … Read More

Machine Learning with Python and Scikit-Learn

Register to attend the workshop at the bottom of this page. Zoom link will be emailed after filling out the registration form. Amarel account: Apply here as soon as possible. VPN setup: You have to be connected on Rutgers' network or be on VPN  to access Amarel resources. SSH setup: Windows users must install an … Read More

Deep Learning with Python and Keras

Register to attend the workshop at the bottom of this page. Zoom link will be emailed after filling out the registration form. Amarel account: Apply here as soon as possible. VPN setup: You have to be connected on Rutgers' network or be on VPN  to access Amarel resources. SSH setup: Windows users must install an … Read More

Amarel monthly maintenance

Anticipated monthly maintenance schedule March 2021 - January 2022: MAR 19-20-21 (3/20 & 3/21 Hill Data Center maintenance, which will affect Amarel users) APR 20-21 MAY 18-19 JUN 15-16 JUL 20-21 AUG 17-18 SEP 21-22 OCT 19-20 NOV 16-17 DEC 21-22 JAN 18-19

Machine Learning Series by OARC—Random Forest Workshop

Please register to attend this workshop at the bottom of this page. After filling out the registration form, we will email you the Zoom link. Amarel account: You need an Amarel account to participate in the lab section Apply here as soon as possible. VPN setup: You have to be connected on Rutgers’ network or … Read More

Clinical informatics – introduction

Workshop 1: Clinical informatics, data science in biomedicine and Advanced computing seriesBranimir Ljubic presents the first workshop: “Clinical informatics – introduction” within the series of workshops: “Clinical informatics, Data science in medicine, Advanced computing.” These workshops will provide theoretical insights and practical advice needed for understanding and successful work in the field of Clinical informatics … Read More

Intro to Linux Command Line

Register to attend this workshop at the bottom of this page. Zoom link will be emailed after filling out the registration form. Amarel account: Apply here as soon as possible. VPN setup: You have to be connected on Rutgers' network or be on VPN to access Amarel resources. SSH setup: Windows users must install an SSH … Read More

Clinical informatics, data science in biomedicine and Advanced computing series – workshop 2

Workshop 2: Computer science in clinical medicine, introduction into Machine learning, Advanced machine learning methods in medicine — review Branimir Ljubic presents the second workshop within the series of workshops: “Clinical informatics, Data science in medicine, Advanced computing." The workshop will cover Prediction of medical conditions using Advanced Machine Learning (ML) Techniques — review of … Read More

HPC in life science—Genomics Series2, Variant analysis on Amarel cluster

Please register to attend this workshop at the bottom of this page. After filling out the registration form, we will email you the Zoom link. Amarel account: You need an Amarel account to participate in the lab section Apply here as soon as possible. VPN setup: You have to be connected on Rutgers’ network or … Read More

Computer science in medicine, introduction into Machine learning, traditional learning models – workshop 3

Workshop 3: Computer science in medicine, introduction into Machine learning, traditional learning models (Decision trees, K-NN, Perceptron, SVM, Bagging - Boosting (random forest, Adaboost), etc.) Branimir Ljubic presents the third workshop: “Computer science in medicine, introduction into Machine learning, traditional learning models (Decision trees, K-NN, Perceptron, SVM, Bagging - Boosting (random forest, Adaboost), etc.)” within … Read More