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Deep Learning with R
Deep Learning with R
  • Syllabus
  • Schedule
  • Readings
  • Code
  • Classes
Class sessions
  • 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
  • Final project

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

Materials from class on Wednesday, June 10, 2020

Slides

Overfitting

Lecture slides in HTML format

Lecture handouts in PDF format

Text

Lecture slides in HTML format

Lecture handouts in PDF format

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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