/cas-dl-compvis-exercises-ss2024

Exercises for CAS DL - Computer Vision with Deep Learning

Primary LanguageJupyter Notebook

Exercises for CAS Deep Learning - Module Computer Vision with Deep Learning (Part 1)

This repository is used for the development and distribution of exercises for the CAS Deep Learning - Module Computer Vision with Deep Learning (Part 1).

There are several ways to work on the assignments:

  • Google Colab (easiest)
  • local - pip install (not tested)
  • local - Docker

Google Colab

Use Google Colab by clicking on the links below.

Exercise 00 - Environment Check

Click on the following badge to open the notebook in Google Colab:

Open In Colab

Exercise 01 - Machine Learning Recap

Click on the following badge to open the notebook in Google Colab:

Open In Colab

Exercise 02 - PyTorch & Machine Learning

Click on the following badge to open the notebook in Google Colab:

Open In Colab

Exercise 03 - Neuronale Netzwerke

Click on the following badge to open the notebook in Google Colab:

Open In Colab

Exercise 04 - Convolutional Neural Networks

Click on the following badge to open the notebook in Google Colab:

Open In Colab

Exercise 05 - Image Classification

Click on the following badge to open the notebook in Google Colab:

Open In Colab

Exercise 06 - Image Classification Practical

Click on the following badge to open the notebook in Google Colab:

Open In Colab

Local - pip (not tested)

pip install -r requirements.txt

Local - Docker

1. Install Docker on your computer

Depending on your operating system you have to install docker in different ways.

You'll find detailed instructions here: https://docs.docker.com/get-docker

2. Pull the Docker image

# pull the image
docker pull mwilli13/cas-dl-compvis-exercises-ss2024:latest

3. Fork this repository

Fork this repository by pressing the fork button on the upper right.

4. Clone your fork to your computer.

Clone into your ml directory (MY_ML_DIR) using:

git clone MY_REPO_FORK_HTTPS_ADDRESS

5. Start a ml container on your machine

# Replace 'MY_ML_DIR' with your local code directory
$ docker run -d \
    -p 8877:8888 \
    --user root \
    -v MY_ML_DIR:/home/jovyan/work/ \
    --name=cas_dl_computer_vision_part1 \
    mwilli13/cas-dl-compvis-exercises-ss2024:latest start.sh jupyter lab --LabApp.token=''

6. Check that your container is running

docker ps -a

7. Connect to your container through your browser

Enter http://localhost:8877/lab in your browser.