Machine learning algorithms are used in many disciplines at the University of Zurich. These algorithms can for example take the form of Naive Bayes classifiers, Random Forests of decisions trees, and Deep Learning Neural Networks, being formulated in languages like Python, R, or Java.
Example Questions:
- Do you use machine learning algorithms in your research, and are you struggling to make your code run efficiently?
- Do you need to know how to build a software environment to use machine learning tools and packages?
- Are you curious about the best way to validate your models and report their accuracy?
- Are you just starting to use the latest in artificial intelligence techniques, and you don't know how or where to begin?
If your research requires the use of machine learning algorithms, our Science IT experts can provide guidance on:
- How to build your software environments
- How to use GPU's with your neural network based models, including how to parallelize them across multiple GPU's
- How to validate the accuracy of your models
- How to integrate your workflows into a scientific cluster
- Specific guidance on languages, models, tools, and packages (with an emphasis on Python and R), if our particular sets of expertise matches your use-case
