Inserts the selected rows in the database based on the selected columns from the input table. Creates a new table if the table does not exist.
Reads the body, headers, and the query string from an HTTP request calling the workflow and outputs it in 3 different tables.
Learns a random forest for regression.
t-SNE is a manifold learning technique, which learns low dimensional embeddings for high dimensional data.
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This node applies Matched Pair transforms to an input table of molecules
Node to cyclise a SMILES string by connecting the first and last atom with a new single bond by inserting a ring closure
Learns an ensemble of decision trees (such as random forest variants).
Creates an agent that utilizes the function calling feature of (Azure) OpenAI chat models.
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