This repository contains notebooks that show how to use the mcfly software. Mcfly is deep learning tool for time series classification..
Currently we here offer two tutorials. Our main tutorial can be found in the notebook notebooks/tutorial/tutorial.ipynb. This tutorial will let you train deep learning models with mcfly on the PAMAP2 dataset for activity recognition.
A comparable, slightly quicker tutorial can be found in the notebook notebooks/tutorial/tutorial_quick.ipynb. This tutorial will let you train deep learning models with mcfly on the RacketSports dataset for activity recognition.
Prerequisites:
- Python 3.5, 3.6, or 3.7
- Have the following python packages installed:
- mcfly
- jupyter
Mcfly can be installed through pypi:
pip install mcfly
See https://github.com/NLeSC/mcfly for alternative installation instructions
The tutorials are provided in Jupyter notebooks, which can be found in the folder notebooks. To use a notebook, first install Jupyter:
pip install jupyter
For more documentation on Jupyter: See the official documentation
Windows users can best use Anaconda 3.6.
- Create a new environment (Environments > Create…)
- Click the play button next to your environment and select ‘Open terminal’
- Type
conda install numpy scipy jupyterand thenpip install mcfly - Click the play button again and select ‘open with Jupyter notebook’
- Navigate to the directory where you cloned this repository, where you can open the notebooks
The tutorials can be run using Jupyter. From the tutorial root folder run:
jupyter notebook
There are two versions of the tutorial. The standard tutorial is for self-learning. There is also a version for workshops which is only expected to be used with the aid of an instructor.