Pattern Recognition Course

Files related to course on pattern recognition.

Setup

1. Setup your python environment using venv

Make sure you have python 3.x installed in your computers and know how to call it from the command line. To create a virtual environment (assuming your run python 3 using python3 from the command line), execute the following command:

python3 -m venv env

This will create a directory called env (which is ignored here in the repository so you can generate your own).

2. Activate your environment

For Linux / Mac users:

source env/bin/activate

For Windows users:

env\Scripts\activate.ps1

If permission problems persist on Windows, you might have to run the following first:

env\Scripts\activate.ps1

3. Install the necessary dependencies.

For each of the following, make sure to run pip install [package-name]:

• jupyter
• pandas
• torch
• tqdm
• sklearn

4. Enter the directory notebooks and run the following command:

jupyter notebook .

5. Visit the running jupyter instance by pointing your browser to http://localhost:8888 (usually this is ran automatically after doing item 4).

Lab Exercises

• Neural Regression