IntroToML

Inroduction to Machine Learning Tutorial repository

This github repository contains code for the Introduction to Machine Learning Tutorial. These examples allow you to explore different algorithms including: Decision Trees Random Forests Neural Networks

Please see the following web page for meetings that have used this repository:

• http://www.sepnet.ac.uk/sepnet-graduate-network/training-events-201920/machine-learning-and-ai-workshop-15-16-january-2020/
• https://indico.stfc.ac.uk/event/175/

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Getting Started:

Clone the repository with the following command to get started with working with these examples. git clone --branch master https://github.com/adrianbevan/IntroToML.git

The examples pertaining to a given algorithm can be found in the different directories:

BDT - decision trees using SciKitLearn

NN - Neural Networks using TensorFlow

Software Requirements:

The Python environment that these tutorials has been tested on is packaged in the Anaconda framework: https://www.anaconda.com

Install Anaconda and then obtain the following packages:

• scikit-plot (conda install -c conda-forge scikit-plot OR pip install scikit-plot)
• opencv (conda install -c conda-forge opencv OR pip install opencv-python)
• keras (conda install -c conda-forge keras OR pip install keras)
• tensorflow (conda install -c conda-forge tensorflow OR pip install tensorflow)
• pydotplus (conda install -c conda-forge pydotplus OR pip install pydotplus)

If you run into any ModuleNotFound errors and cannot work out which packages you are missing please call over someone to help you.

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Authors: Adrian Bevan (a.j.bevan@qmul.ac.uk) Joe Davies (j.m.m.davies@qmul.ac.uk)

Copyright (C) Queen Mary University of London

This code is distributed under the terms and conditions of the GNU Public License