During this webinar, we will guide you through the complete journey of a data scientist: from training and selecting the best machine learning model for your data to putting your model into production and creating a simple web application.
For this, we will demonstrate a use case of bioactivity prediction.
- Train and optimize four different machine learning methods (Naive Bayes, Logistic Regression, Random Forest, XGBoost)
- Identify the best model to predict the activity of a compound on a particular biological target
- Use KNIME’s new integrated deployment functionality to automatically deploy the best model
- Create a simple web application that uses the deployed model to predict the activity of new compounds
The webinar will round off with a Q&A session. We look forward to lots of questions!
This webinar is partially supported by de.NBI: the German Network for Bioinformatics Infrastructure.
You’ll receive a zoom link with your registration confirmation. Make sure you have a stable internet connection!
Absolutely - fire away!
Download the latest free, open source version of knime here: knime.com/download