Programming environment
This guide is for setting up your own machine with the software needed to work through the weekly and mandatory exercises in IN4080 Natural Language Processing. For most of our work, we will use Python, extended with various packages.
We recommend you to install the environment on your own computer. This setup is covered in the section Setup with Anaconda below. You can also work on the IFI machines. Details about this option are available at the end of this document.
Setup with Anaconda
Download and install either Anaconda or Miniconda
For the differences between the two, see here.
Follow the online guides to install Anaconda or Miniconda. Once you have a working shell with Conda installed, you can continue here.
You should now have access to the conda command. For a quick test, execute the conda command without any arguments.
conda
You are recommended to download the conda cheat sheet and keep it at hand.
Create environment
Make sure that you are in the directory with the environment.yml file that you can download here.
The following command will create an environment named in4080_2024 with all the Python modules that we'll use in the course.
conda create --name in4080_2024
Activate the environment
To activate the environment
conda activate in4080_2024
If you want to get back to your standard Python and packages:
conda deactivate
Installing packages
We can add packages while creating an environment
conda create --name in4080_2024 python<=3.9 numpy pandas
- python<=3.9 will specify which version of python you want for your environment.
Install packages into a previously created environment either by activating the environment you want to modify or specifying the environment name on the command line:
# via environment activation
conda activate in4080_2024
conda install matplotlib
# via command line option
conda install --name in4080_2024 matplotlib
In Windows you can choose the environment from the start menu. There is also an option to open Jupyter Notebooks directly in your browser. This is the recommended way of working in this course.
Working on IFI machines
Please contact the course teachers to get access to the machines. The information below is from previous years and may be outdated.
IFI?machines
On an IFI terminal, the default python is now
opt/ifi/anaconda3/bin/python3
This means that when you start a python/jupyter notebook session, you get access to all these packages.
Remote login
You may login remotely to the IFI-machines when working from home. The recommended solution is now to use VDI, see here
It will (eventually) give you access to the same environment as when you login directly to an IFI linux machine. However, you will not have access to the /projects/nlp/. You will have to download data within nltk when needed.