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Preparatory Lab for NTUA Pattern Recognition and Speech and Language Processing

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Python - Numpy - Bash introductory Lab

This is the introductory lab for Pattern Recognition and Speech and Language Processing in NTUA. Material covers an introduction to Python, NumPy and matplotlib. It also covers a short introduction to Bash scripting.

Some of the material is adapted from this tutorial in cs231n course at Stanford.

Folder structure:

.
├── bash       # Short introduction to bash scripting
├── python     # Introduction to Python, numpy, scikit-learn and Pytorch
├── README.md  # This file
└── vm         # Vagrantfiles for setting up a Linux Virtual Machine

Course Virtual Machine

To ease the setup process we provide a virtual machine for each course with the required software preinstalled.

All relevant files / scripts are located inside the vm folder.

To run the virtual machine you need to download and install Vagrant and VirtualBox. Then you need to open a terminal and run:

# For Pattern Recognition course
cd <path/to>/python-lab
cp Vagrantfile.patreco Vagrantfile
vagrant up

or

# For Speech and Language Processing course
cd <path/to>/python-lab
cp Vagrantfile.slp Vagrantfile
vagrant up

Setup will take a while, since it installs all dependencies.

When the setup is finished, a jupyter notebook will start in the machine. Navigate to the URL printed.

Changes to files will be saved automatically to your current working directory.

To access the console inside the VM use

vagrant ssh

To stop the VM use

vagrant halt

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