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Matt Graham e8333c02f1 Squashed commit of fixes to allow lab 1 notebook to render on Github.
commit eb66a44a9f899e20457576a3d34ceb33e0b46004
Author: Matt Graham <m.m.graham@ed.ac.uk>
Date:   Mon Oct 3 12:17:55 2016 +0100

    Restoring output without static function definitions.

commit 623748b334b7f0667c0b2d6e2f829a49978e87eb
Author: Matt Graham <m.m.graham@ed.ac.uk>
Date:   Mon Oct 3 12:16:29 2016 +0100

    Removing loaded static function definitions to test if helps Github rendering.

commit 9b4c21b97e7766ba20db00f80bbd31081417c269
Author: Matt Graham <m.m.graham@ed.ac.uk>
Date:   Mon Oct 3 12:14:42 2016 +0100

    Removing outputs from notebook to check if allows Github to render.
2016-10-06 12:30:05 +01:00
data Adding CCPP data and data provider. 2016-09-28 05:07:01 +01:00
mlp Switching from 'cost' to 'error' for consistency with slides. 2016-09-30 02:53:13 +01:00
notebooks Squashed commit of fixes to allow lab 1 notebook to render on Github. 2016-10-06 12:30:05 +01:00
.gitignore 1st labs 2015-09-27 22:00:09 +01:00
environment-set-up.md Further clarifying reload vs. import note. 2016-09-27 19:15:28 +01:00
quota-issue.md Changing to using remove rather than clean in quota issue fix based on lab feedback. 2016-09-27 19:02:22 +01:00
README.md Small fixes to initial description. 2016-09-20 12:54:51 +01:00
setup.py Adding additional authors to metadata. 2016-09-21 00:53:52 +01:00

Machine Learning Practical

This repository contains the code for the University of Edinburgh School of Informatics course Machine Learning Practical.

This assignment-based course is focused on the implementation and evaluation of machine learning systems. Students who do this course will have experience in the design, implementation, training, and evaluation of machine learning systems.

The code in this repository is split into:

  • a Python package mlp, a NumPy based neural network package designed specifically for the course that students will implement parts of and extend during the course labs and assignments,
  • a series of Jupyter notebooks in the notebooks directory containing explanatory material and coding exercises to be completed during the course labs.

Getting set up

Detailed instructions for setting up a development environment for the course are given in this file. Students doing the course will spend part of the first lab getting their own environment set up.