Maarit WidmanninLow Code for Data ScienceUnderstanding and Applying Correspondence AnalysisA low-code approach to analyze associations in categorical data by projecting the categories of the variables onto new numeric dimensionsJul 26, 20231Jul 26, 20231
Maarit WidmanninLow Code for Data ScienceHow to Create Workflow & REST Services with KNIMEA guide to service orchestration with KNIMEJul 17, 2023Jul 17, 2023
Maarit WidmanninLow Code for Data ScienceCertify Your KNIME Time Series Analysis ExpertiseThe new KNIME L4-TS Certification ExamJun 23, 2023Jun 23, 2023
Maarit WidmanninLow Code for Data ScienceGenerate synthetic data to teach machine learningUse KNIME Verified components for ease of reusability and sharingJun 5, 2023Jun 5, 2023
Maarit WidmanninLow Code for Data ScienceThree More Techniques for Data Dimensionality Reduction in MLImplementing LDA, Neural Autoencoder, and t-SNE in a codeless fashionOct 7, 2022Oct 7, 2022
Maarit WidmanninLow Code for Data ScienceSeven Techniques for Data Dimensionality ReductionA codeless KNIME solution to work with datasets with thousands of columnsSep 30, 20221Sep 30, 20221
Maarit WidmanninLow Code for Data ScienceEasy Interpretation of a Logistic Regression Model with Delta-p StatisticsUnderstand and assess easily the individual effects that make a credit application succeed or failJul 15, 2022Jul 15, 2022
Maarit WidmanninLow Code for Data ScienceCohort Analysis: Seeing the Forest for the TreesRevealing a comprehensive view of your business with KNIMEJun 22, 2022Jun 22, 2022
Maarit WidmanninLow Code for Data ScienceBuilding a Time Series Analysis ApplicationDescribing the process of accessing, pre-processing, and forecasting time seriesJun 15, 2022Jun 15, 2022
Maarit WidmanninLow Code for Data ScienceFrom Modeling to Scoring: Correcting Predicted Class Probabilities in Imbalanced DatasetsCorrect the predicted class probabilities by the information on the a priori class distributionMay 4, 2022May 4, 2022
