Deep Learning

This repository serves as a summary or a look up reference to the deep learning lecture of the HTW Saar (Sommersemester 2021 - Praktische Informatik (applied computer science)).

Environment Setup

Python version 3.8 is required

To execute the code samples in python files or jupyter notebooks, setup a virtual environment with the required packages. The virtual environment can either be done directly via anaconda (environment.yml) or manually by installing the packages via pip.

Setup with anaconda

1. Make sure an Anaconda distribution is installed on your machine. (either anaconda or miniconda)
2. Create the Anaconda environment with: conda env create -f environment.yml
   The environment name is specified on top of the environment.yml and defaults to DL
3. Activate the environment with: conda activate DL

Setup manually

1. Create a virtual environment of your choice.
2. Activate your environment
3. Install with pip by executing the following: pip install -r requirements.txt

Machine Learning Fundamentals

Representational Learning

Neural Networks

Convolutional Neural Networks (CNN)

Recurrent Neural Networks (RNN)

Feed Forward Neural Networks (FFN)

Project