/slides-rmcs-litreview

Presentation titled "A Brief Review of Hyperparameter Optimization Methods for Machine Learning" for Research Methods in Computer Science course at Ryerson University

Primary LanguageHTMLMIT LicenseMIT

A Brief Review of Hyperparameter Optimization Methods for Machine Learning

Richard Wen
rwen@ryerson.ca

Presentation slides for Research Methods in Computer Science Course Instructed by Dr. Cherie Ding.

Build Status GitHub license Twitter

Install

  1. Install npm
  2. Clone this repository
  3. Install dependencies with npm
git clone https://github.com/rrwen/slides-rmcs-litreview
cd slides-rmcs-litreview
npm install

Usage

  1. Generate docs/index.html (see script.html in package.json)
  2. Generate slides/wen2017_hyperoptml_slides.pdf (see script.pdf in package.json)
npm run html
npm run pdf

See Edits and Implementation for more details.

Developer Notes

Edits

The following can be edited before generating:

  • slides/wen2017_hyperoptml_slides.md: Markdown file with slide contents
  • slides/template.html: Custom reveal-md template
  • docs/edit/style.css: CSS file to adjust styling of slides
  • docs/edit/logo.png: logo image to use

Implementation

The slides slides-rmcs-litreview uses the following npm packages for its implementation:

npm Purpose
reveal-md Converting slides/wen2017_hyperoptml_slides.md to docs/index.html
decktape Converting slides/wen2017_hyperoptml_slides.md to slides/wen2017_hyperoptml_slides.pdf
windows-build-tools Compiling dependencies for decktape on Windows Operating System (OS) 
       reveal-md            <-- Convert markdown  slides to html

       decktape             <-- Convert markdown slides to pdf
          |
  windows-build-tools       <-- Compile decktape on Windows OS