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/
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-plotORpip install scikit-plot) - opencv (
conda install -c conda-forge opencvORpip install opencv-python) - keras (
conda install -c conda-forge kerasORpip install keras) - tensorflow (
conda install -c conda-forge tensorflowORpip install tensorflow) - pydotplus (
conda install -c conda-forge pydotplusORpip 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.
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