fyquah / stanford_dl_ex

Programming exercises for the Stanford Unsupervised Feature Learning and Deep Learning Tutorial

stanford_dl_ex Solutions

This is a fork of stanford_dl_ex with the solutions for Stanford UFLDL Exercises.

Note that these are NOT the official solutions : they are simply solutions which I have coded and worked decently to give me reasonable solutions.

Note that this repository is made for Octave . Mose functionalities should work equally fine on Matlab, but I have not tested them on Matlab.

Setting up

1. Clone this repository
2. Compile optimizers used throughout this code base:

cd path/to/repository/stanford_dl_ex/common/minFunc_2012
octave mexAll.m
# This will start some prerequiste files

3. Install the io and statistics package (used for randsample in gradient checking subroutines)

# in Any Directory
octave # enter the octave Prompt
octave:1> pkg install -forge io
octave:1> pkg install -forge statistics

Core Codebase Changes

In addition to solving the problems, I have made some changes to adapt the codebase for Octave.

1. Change mex -outdir ... into mex -o ... in mexAll.m
2. Manually load statistics package in grad_check.m