This workshop will cover some of the tools and workflow for getting started with applied ML. Attendees will learn how to use jupyter notebooks, and the scientific python ecosystem to experiment with machine learning.
Learning outcomes
This workshop assumes:
The easy way of getting everything you need for this workshop is by the way of installing Anaconda.
Alternatively, you can manually install the following components.
Graphviz, also make sure that you have added it to the PATH
SciPy pip3 install scipy
Matplotlib pip3 install matplotlib
NumPy pip3 install numpy
pandas pip3 install pandas
Scikit-learn pip install -U scikit-learn
Jupyter Notebooks pip3 install jupyter
This repository will present an applied introduction to machine learning.
Applied example which shows, via a Jupyter notebook:
The majority of this workshop will be taught through the use of a Jupyter notebook, which you can download from here. Everything you need is in the examples
folder.
Alternatively, you can clone the repository using Git:
git clone https://github.com/hackersatcambridge/workshop-python-ml