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Deep Learning with R
Deep Learning with R
  • Syllabus
  • Schedule
  • Readings
  • Code
  • Classes
Reading details
  • References
Readings
  • Day 1: Fundamentals of Deep Learning I
  • Day 2: Fundamentals of Deep Learning II
  • Day 3: Overfitting, regularization, dropout, pretrained models, word embedding
  • Day 4: Convolutional Neural Networks, images
  • Day 5: Generative Adversarial Networks, Autoencoders, Recurrent Neural Networks, LSTM, GRU, sequence learning

Day 3: Overfitting, regularization, dropout, pretrained models, word embedding

Read before class on Wednesday, June 10, 2020
  • Deep learning with R: Chapter 4.4 - Overfitting and underfitting
  • Deep learning with R: Chapter 4.5 - The universal Deep Learning workflow
  • What Are Word Embeddings for Text?

Last updated on June 10, 2020

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BIOS 691: Deep Learning with R (Summer 2020)
Virginia Commonwealth University    Biostatistics Graduate Program

Dr. Mikhail Dozmorov    mdozmorov@vcu.edu

Monday through Friday    9:00am – 12:00pm
Online

All content licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Content 2020 MGD

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