Resources for the MDB Machine Learning Workshop for April 6th 2019.
To start, clone this repository. We'll be working out of it for the workshop.
To follow good practice, we'll be working out of virtual environment for the following reasons:
- Leaving your global python installation the same
- Ensuring that we are all working with the same exact packages
- Prevent versioning conflicts. Specifically, we're using tensorflow 2.
- Make sure you have python 3.6 or python 3.7 on your computer.
- Make sure you have
pipforpython3installed on your computer. As I have bothpythonandpython3on my computer, for me this ispip3 - Then, install the virtualenv package with
pip install virtualenv. Ideally, this is the only package you have on your system level python installation. You can figure out what pip packages you currently have installed by runningpip freeze. Ideally, the output list should only containvirtualenv, though that's probably not the case.
- Create a virtual environment called
venvin the github repository by runningpython3 -m virtualenv venv. - Activate the virtual environment by running
source venv/bin/activate. You can always deactivate the virtual environment withdeactivate. - Install all the packages for this workshop by running
pip install -r requirements.txt. This will install all packages needed for the workshop!
Finally, we're going to be using some datasets during the workshop and its best if you have them downloaded before hand.
To make sure the data sets are on your system, with your virtual environment active run python load_datasets.py.
You should see some datasets being downloaded through the Keras package. That's all you need to do!
We will work out of jupyter notebooks. Run jupyter notebook in the virtual environment from the mlworkshop directory.