/ai_for_smart_health

My fork of the course AI for Smart Health including all Notebooks and Datasets

Primary LanguageJupyter NotebookMIT LicenseMIT

Intelligent Systems for Smart Health

Materials and tests to support the course at Düsseldorf University of Applied Sciences (HSD).

Create new environment for this course (recommended)

It is recommended to create a new environment for this course with many Python libraries that we will use in the Live Coding sessions. You can simply download the environment.yml file in this repository, or clone the repository using:

git clone https://github.com/florian-huber/ai_for_smart_health.git

Then, in the folder with the environment.yml file simply run:

conda update -n base -c defaults conda  # optional (to make sure conda is up to date)
conda env create -f environment.yml

This should create a Python 3.9 environment with the packages listed in the yaml-file.

Hardware & performance

This course will include a lot of machine learning, mostly also deep learning. For this, we will work with the Python libraries scikit-learn (classical machine learning) and Tensorflow (deep learning).

Scikit-learn can be accelerated using scikit-learn-intelex (https://intel.github.io/scikit-learn-intelex), although this will not be needed for the live coding sessions we do.

Tensorflow can make use of NVIDIA graphic cards, which can greatly enhance deep learning model training. While this allows us to use a lot of low-level optimization, it can be tricky and time consuming to get this up and running.

Für alle die auch Probleme mit dem shap Package auf Windows hatten: Ich bekomme es jetzt zum laufen, indem ich diese beiden .yml files nacheinander in einem frischen conda environment installiere. create_environment.yml installiert nur python, llvmlite, numba und shap. Diese 3 Packages vertragen sich irgendwie nicht so gut. Die zweite .yml file installiert dann alle anderen packages aus dem ursprünglichen environment.yml. 

 

shap Troubleshooting

If you can't import shap in the environment you have created, try to create it this way:

conda update -n base -c defaults conda
conda env create -f create_environment.yml
conda activate ai4sh
conda env update --file update_environment.yml --prune