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DATE/TIME:
August 6, 2020
DESCRIPTION:
Learn how you can apply multiple tools to perform EDA tasks on publicly available datasets.
LENGTH: 90 minutes
PRESENTER: George Zaki, PhD
LEVEL OF DIFFICULTY: Beginner
DATE/TIME:
July 31, 2020
DESCRIPTION:
The Predictive Oncology Model and Data Clearinghouse (MoDaC) is a data repository and model clearinghouse developed to transition resources to the broader research community. These resources consist of predictive oncology datasets and mathematical models (such as machine learning and deep learning models) developed within NCI and in collaborative programs.
LENGTH: Self-paced
PRESENTER: MoDaC Team, Ruth S. Frost
LEVEL OF DIFFICULTY: Beginner
DATE/TIME:
July 16, 2020
DESCRIPTION:
Learn about the concepts and tools in machine learning to generate molecular descriptors for drug function classification.
LENGTH: Two hours
PRESENTER: Sarangan Ravichandran, PhD, PMP
LEVEL OF DIFFICULTY: Beginner
DATE/TIME:
March 3, 2020
DESCRIPTION:
Learn about a practical approach for evaluating deep learning methods for nucleus segmentation using state of the art neural networks.
LENGTH: One hour
PRESENTER: George Zaki, PhD
LEVEL OF DIFFICULTY: Intermediate
DATE/TIME:
July 22, 2019
DESCRIPTION:
Learn how to use Pandas for Exploratory Data Analysis.
LENGTH: Two hours
PRESENTER: Bari J. Ballew
LEVEL OF DIFFICULTY: Beginner
DATE/TIME:
April 21, 2019
DESCRIPTION:
Learn the basics of data science for cancer research.
LENGTH: Two days
PRESENTER: Mark Jensen, PhD, Randall Johnson, PhD, Martin Skarzynski, PhD, Simina Boca, PhD, Bari J. Ballew, PhD, Subhasis Ray, PhD
LEVEL OF DIFFICULTY: Beginner