{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Deep Learning Packages Intro." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "* [손고리즘] middle learning - 파이썬을 이용한 기계학습 알고리즘 기초\n", "* 김무성" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# theano & caffe" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 1. theano" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "* Intro\n", "* Tutorial – Learn the basics\n", "* Deep Learning Tutorials Using theano\n", "* Related-projects" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 1.1 Intro" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "http://deeplearning.net/software/theano/" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "* Theano and PyLearn - http://hunch.net/~nyoml/theano.pdf\n", "* Theano and PyLearn future plans - http://hunch.net/~nyoml/theano_2.pdf\n", "* Colin Raffel tutorial on Theano - http://deeplearning.net/software/theano/\n", "* Theano Tutorials Session 1 - https://drive.google.com/file/d/0B64011x02sIkdDB5MmdnRnNTbWc\n", "* Theano Tutorials Session 2 : Advanced usage - https://drive.google.com/file/d/0B64011x02sIkOVpPY1B2WmVYa3c \n", "* Theano Tutorials Session 3 : Internals - https://drive.google.com/file/d/0B64011x02sIkWW9LLVV6QWtzRTg" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 1.2 Tutorial – Learn the basics" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "http://deeplearning.net/software/theano/tutorial/index.html#tutorial" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 1.3 Deep Learning Tutorials Using theano" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "http://www.deeplearning.net/tutorial/" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 1.4 Related-projects" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "https://github.com/Theano/Theano/wiki/Related-projects" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 2. caffe" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "* Intro\n", "* Tutorial\n", "* EXamples" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "## 2.1 Intro" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "http://caffe.berkeleyvision.org/" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "* web demo - http://demo.caffe.berkeleyvision.org/\n", "* DIY Deep Learning for Vision with Caffe : Tutorial presentation - https://docs.google.com/presentation/d/1UeKXVgRvvxg9OUdh_UiC5G71UMscNPlvArsWER41PsU/edit#slide=id.p" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 2.2 Tutorial" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "* Tutorial Documentation : Practical guide and framework reference - http://caffe.berkeleyvision.org/tutorial/\n", "* Installation instructions : Tested on Ubuntu, Red Hat, OS X - http://caffe.berkeleyvision.org/installation.html\n", "* Model Zoo - https://github.com/BVLC/caffe/wiki/Model-Zoo" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 2.3 Examples" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "* ImageNet tutorial : Train and test \"CaffeNet\" on ImageNet data - http://caffe.berkeleyvision.org/gathered/examples/imagenet.html\n", "* ImageNet classification : Use the pre-trained ImageNet model to classify images with the Python interface - http://nbviewer.ipython.org/github/BVLC/caffe/blob/master/examples/classification.ipynb\n", " " ] } ], "metadata": { "kernelspec": { "display_name": "Python 2", "language": "python", "name": "python2" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 2 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython2", "version": "2.7.3" } }, "nbformat": 4, "nbformat_minor": 0 }