JKISeasor2-24_tomljh_ver2
Challenge 24: Fraudulent Email Address Detection
JKISeasor2-24_tomljh_ver1
Challenge 24: Fraudulent Email Address Detection
kn_deeplearn_010_prepare_adult_dataset
Prepare the "adult" or "census-income" dataset for the use in deep learning nodes and models. Convert numbers to double and do a label enconding on the […]
03 Data pipeline orchestration
<p>Once the ETL on new customer data workflow is executed successfully, i.e., customer data are extracted and anonymized, and the database table "customers" […]
03 Data pipeline orchestration
<p>Once the ETL on new customer data workflow is executed successfully, i.e., customer data are extracted and anonymized, and the database table "customers" […]
Monitoring
Monitoring workflow. This workflow monitors the performance of the model based on different metrics. For the data where the ground truth is available, it […]
Monitoring
Monitoring workflow. This workflow monitors the performance of the model based on different metrics. For the data where the ground truth is available, it […]
Monitoring
Monitoring workflow. This workflow monitors the performance of the model based on different metrics. For the data where the ground truth is available, it […]
Bioluminate 1
The antibody structure can be split into Fc, Fab and Fv domains. The node scans proteins for residues that are candidates for mutation and evaluate the […]
Bioluminate 1
The antibody structure can be split into Fc, Fab and Fv domains. The node scans proteins for residues that are candidates for mutation and evaluate the […]