IdentifyNuclei_measure2Channels
You can vizualize any of your intermediate results. Please specify the objects and the images in the metanode.
Titanic_065_Phase_6_Deployment_Preparation_v4
Titanic: Phase 6 (Deployment) Preparation v4 URL: Data Science Training - Kapitel 6 https://data-science.training/kapitel-6/
Titanic_057_Phase_3_Data_Preparation_v4
Titanic: Phase 3 (Data Preparation) v4 URL: Data Science Training - Kapitel 5 https://data-science.training/kapitel-5/
06_Connecting_to_Databricks
This workflow shows how to connect to a Databricks cluster and utilize various KNIME nodes to interact with Databricks from within KNIME Analytics […]
miRcorrNet_v11
miRcorrNet: Machine Learning-based Integration of miRNA and mRNA Expression Profiles, Combined with Feature Grouping and Ranking This workflow allows you […]
PCA w Correlations
This workflow applies PCA dimensionality reduction to reduce the dataset dimensions from three to two features. Data points are then displayed in a […]
kn_example_python_flow_variable_if_switch
Three ways to handle combination of Flow variables from Python and If switches In one Python environment a Flow Variable for the usage in KNIME will be […]
04_Advanced_Row_Filters
Showcase of various advanced row filtering approaches on different data types featuring a variety of Row Filter nodes.
PCA w Correlations
This workflow applies PCA dimensionality reduction to reduce the dataset dimensions from three to two features. Data points are then displayed in a […]