tsne_presentation

KO | EN

gitlite — search

#javascript #python #hacktoberfest #react #ai #typescript #llm #android #docker #java #windows #awesome #vue #openai

tsne_presentation

(★ 9)

Quick & dirty repo for hosting the Notebook for t-SNE presentation at delivered at Python Quants and PyData London meetups

tsne_presentation 최신버젼 다운로드

최종 버전 다운로드 (.zip)

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

# t-SNE Presentation

_Personal Project for t-SNE Demonstration_

Barebones repo for hosting the Jupyter Notebook and presentation of my t-SNE presentation delivered at Python Quants and PyData London meetups 2015 & 2016

Demo of high dimensional data visualisation with t-distributed Stochastic Neighbor Embedding (t-SNE) using the [Urban Land Cover Classification](https://archive.ics.uci.edu/ml/datasets/Urban+Land+Cover) dataset from the UCI Machine Learning Repository.

This is also a small example of using RISE to present a Jupyter Notebook.
RISE is quite new, available at https://github.com/damianavila/RISE

# A. Simplest usage: view the content in Github

1. Open the Github page for the `tsne_presentation.ipynb` file
2. Github magically renders the file to static HTML for reading

# B. Slightly more advanced usage: download and run the `reveal.js` based presentation

## Git clone the repo to your workspace.

e.g. in Mac OSX terminal:

$> git clone https://github.com/jonsedar/tsne_presentation.git
        $> cd tsne_presentation

## Using a basic webserver, locally host the `tsne_presentation.slides.html` file

e.g. in Mac OSX terminal, use Python's inbuilt webserver

$> python -m http.server      (if using Python 3)
        or
        $> python -m SimpleHTTPServer  (if using Python 2)

Then open `localhost:8000/tsne_presentation.slides.html` in your webbrowser

## Optionally compile a static presentation using plain old reveal.js

1. At the terminal, use nbconvert:

$> ipython nbconvert tsne_presentation.ipynb --to slides

This creates `tsne_presentation.slides.html` which you can serve as above

# C. Execute the Notebook for yourself and use RISE to present

## Setup a virtual environment for this project

**NOTE:** requires Python 3.5 for RISE to correctly work

Using Anaconda distro, create a new virtualenv, installing packages using YAML file:

$> conda env create --file conda_env_tsne_presentation.yml
        $> source activate tsne_presentation

## Install RISE

1. Clone the RISE repo https://github.com/damianavila/RISE
2. Source activate your python environment (if not already done)
3. Run `python setup.py install` from within the cloned RISE directory, this will install the nbextension into your virtualenv

## Edit or rerun the Notebook

1. Run `$> ipython notebook` as normal, open `tsne_presentation.ipynb` and
make edits, re-run etc as you wish

## View the RISE presentation

1. Click the newly added button within the Notebook menu "Enter/Exit Live Reveal Slideshow"
2. Be sure to check out the interactive elements on the grouped boxplots and the 3D scatterplot.
3. You can also double-click into the Notebook cells and edit them live, if you wish

For any more details get in touch: jon.sedar@applied.ai

tsne_presentation

tsne_presentation 최신버젼 다운로드

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

tsne_presentation

tsne_presentation 최신버젼 다운로드

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

Download README