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  • Discoverability Visible
  • Join Policy Open/Anyone
  • Created 08 Sep 2021

The presentation is now available.

In this workshop, you will learn about:

  1. Building blocks of Convolutional Neural Networks
  2. Virtual environment for installation of Python packages and deep learning frameworks (Tensorflow and Keras)
  3. Downloading data to your local storage and feeding the data to your network
  4. Splitting data into training, validation, and testing sets
  5. Defining Deep Neural Network architecture
  6. Training models using training data
  7. Evaluating models using validation data
  8. Saving trained models
  9. Making predictions using testing data with trained models
  10. Transfer learning

Date:               Wednesday, November 6, 2019
Time:               1:30-3:00 p.m.
Location:         NCI Shady Grove, Seminar 110

Instructor: Hyun Jung, Ph.D, Bioinformatics Analyst IV, Imaging and Visualization Group, Advanced Biomedical Computational Science Group,Biomedical Informatics and Data Sciences (BIDS) Directorate, Frederick National Laboratory for Cancer Research (FNLCR).

Questions? Contact the NCI Data Science Learning Exchange

Created by Clint Malone Last Modified Fri December 3, 2021 12:03 am by Clint Malone