yejg2017 / practical3

Optimization and logistic regression

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Practical 3

Machine Learning, spring 2015


Setup will be the same as last time in practical 1. Please refer to the practical 1 repository, and run the script as instructed last time.

We will use the Torch package gnuplot for plotting; you may use (advanced: recommended to try at home instead or if you have time afterwards) iTorch instead as the script installs it.


See simple_example.lua for the example mentioned in the "Introduction" part of the writeup, and practical3.lua for the template for the primary task.

We'll be classifying handwritten digits in a dataset called MNIST, which look like the following:


Each datapoint is a 32x32 image in the version of MNIST we have. The code provided will turn this into a vector containing all the raw pixel values. In simple_example.lua, there is a line containing the word "UNCOMMENT" illustrating how to view a digit from the train/test sets.

See course page for practicals


Optimization and logistic regression


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