Machine Learning Workshop

Workshop on Machine Learning at the Faculty of Mathematics, Warsaw University of Technology - 28 May 2019. Run the notebook from workshops here:

Materials

Workshop materials: Machine-Learning-Worhshops-MINI

Running the notebook

If you want to run your notebook from the workshop remotely click on the banner at the top and if you want to run it locally you will have to do some things:

Fork

Fork my repo

Git

Click on the link and follow the instuctions. I recommend to mark Git Bash during installation and use this console. If you already do it, clone the forged repository:

git clone https://github.com/YOUR_GITHUB_USERNAME/Machine-Learning-Workshop-MINI.git

YOUR_GITHUB_USERNAME - That’s your name on the GutHub - because the repo is in your account..

Conda

We’ll use Conda to install all the necessary Python packages. I strongly recommend installing MiniCondy, unless someone is a mega fan of the GUI then they can install Anaconda Navigator.

Here is link, choose a version for Python 3.7. To verify the installation, run Anaconda Promt (Win + “Anaconda Prompt”) or on a regular console if you are using Linux or MacOS and type:

conda -V

Make sure you have the latest version if you don’t make an update:

conda update conda

Environment

If you managed to install the conda correctly, we will now install a virtual environment with Python and packages. Run Anaconda Prompt, go to the folder with the downloaded repository and type:

conda env create -f workshop-env.yml

This command will create an environment and install the packages.

Running it up

• Once you’ve managed this, enter the repository directory, click Ctrl + L, type cmd, press Enter. If you are on Linux or Mac open command line in folder with forked repo.

• If you’re not scared of what popped up on the screen, that’s great, let’s go.

• Type activate workshop-env (If no such command is found, it means you have to add conda to the environment variables - link)

• Then just run our notebook with a command jupiter notebookthen choose WorkShopMerge.ipynb and enjoy our notebook.

Acknowledgements

Paulina Tomaszewska - Linear Regression

Aleksander Tym - Clustering

Michał Fijałkowski - Organization and Marketing