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Practicing Data Science
Random forest Internet of Things IoT NLP Natural Language Processing
+4
  1. Workflow
    Analyze Data by Training a Decision Tree Classifier for Churn Prediction
    Customer Intelligence CI Churn
    +5
    This workflow is an example of how to train a basic machine learning model for a churn prediction task. In this case, we use a De…
    knime > Beginners Space > 04_Analyze > 01_Analyze_Training_a_Churn_Predictor
    5
  2. Workflow
    Customer Segmentation
    Clustering K-Means Customer segmentation
    +7
    This workflow performs customer segmentation by means of k-Mean clustering. The second part of the workflow implements an interac…
    knime > Examples > 50_Applications > 24_Customer_Segmentation_Use_Case > 02_Customer_Segmentation_Use_Case
    5
  3. Workflow
    Sentiment Analysis (Classification) of Documents
    Sentiment analysis NLP Natural Language Processing
    +2
    This workflow shows how to import text from a csv file, convert it to documents, preprocess the documents and transform them into…
    knime > Examples > 08_Other_Analytics_Types > 01_Text_Processing > 03_Sentiment_Classification
    4
  4. Workflow
    Taxi demand prediction training workflow
    Demand prediction Random forest Time series prediction
    +5
    In this use case, we will use the NYC taxi dataset and a Random Forest to train a simple time series prediction model to predict …
    knime > Examples > 10_Big_Data > 02_Spark_Executor > 11_Taxi_Demand_Prediction > Training_workflow
    3
  5. Workflow
    Validating KNIME Workflows
    Reproducibility Validation Testing
    +3
    This workflow demonstrates a technique to deploy a model prediction workflow as a web service and to validate that it is doing wh…
    knime > Examples > 50_Applications > 51_Model_Deployment_and_Validation > 01_Deploying_and_Validating_models_as_WebServices
    3
  6. Workflow
    Taxi demand prediction deployment
    Demand prediction Random forest Time series prediction
    +5
    In this use case, we will use the NYC taxi dataset and a Random Forest to train a simple time series prediction model to predict …
    knime > Examples > 10_Big_Data > 02_Spark_Executor > 11_Taxi_Demand_Prediction > Deployment_workflow
    2
  7. Workflow
    Document Classification: Model Training and Deployment
    NLP Natural Language Processing Text Classification
    +1
    The goal of this workflow is to do spam classification using YouTube comments as the dataset. The workflow starts with a data tab…
    knime > Examples > 08_Other_Analytics_Types > 01_Text_Processing > 02_Document_Classification
    2
  8. Workflow
    Visualizing Twitter Network with a Chord Diagram
    Data Visualization Twitter Dataviz
    +7
    In this workflow we will: - Read the dataset listing tweets with hashtag #KNIME around the week of July 12, 2018 - Row filter and…
    knime > Examples > 50_Applications > 19_TwitterAnalysis > 03_Visualizing_Twitter_Network_with_a_Chord_Diagram
    2
  9. Workflow
    Basic Customer Segmentation
    Clustering K-Means Customer segmentation
    +3
    This workflow implements a basic customer segmentation through a clustering procedure. No input is required from the business ana…
    knime > Examples > 50_Applications > 24_Customer_Segmentation_Use_Case > 01_Basic_Customer_Segmentation_Use_Case
    2
  10. Workflow
    Anomaly Detection. Time Series AR Testing
    Anomaly detection Time series analysis Auto-regressive models
    +6
    This workflow tests the performance of previously trained auto-regressive models for anomaly detection: - Filter the data to the …
    knime > Examples > 50_Applications > 17_AnomalyDetection > 03b_Time_Series_AR_Testing
    2
  11. Workflow
    Twitter Data Collection
    Twitter NLP Text processing
    +5
    This workflow is designed to collect and store a sample of tweets on a particular search term. With each execution of the workflo…
    knime > Examples > 50_Applications > 19_TwitterAnalysis > 01_Collecting_data_from_Twitter
    2
  12. Workflow
    Topic Detection LDA: Summarizing Romeo & Juliet or cataloging News
    Topic detection Text summarization LDA
    +4
    The workflow shows two examples for the Topic Extrator (Parallel LDA) node. The first workflow extracts topics from the "Romeo & …
    knime > Examples > 08_Other_Analytics_Types > 01_Text_Processing > 25_Topic_Detection_LDA
    1
  13. Workflow
    Risk Scoring: Estimation of Probability of Default
    Risk Scoring Risk assessment
    +5
    The probability of default is a metric that lenders use to assess risk on customers, group them into similar risk bands, and dete…
    knime > Examples > 50_Applications > 38_Credit_Risk_Assessment > Credit_Scoring_Training
    1
  14. Workflow
    Fraud Detection: Model Deployment
    Fraud Fraud detection Random forest
    +5
    This workflow, the deployment workflow, reads the trained model, as well as the new transaction and applies the model to classify…
    knime > Examples > 50_Applications > 39_Fraud_Detection > 02_Fraud_Detection_Deployment
    1
  15. Workflow
    Movie Recommendation Engine with Spark Collaborative Filtering
    Retail Association rules Recommandation engine
    +10
    Creates a Recommendating Engine using Spark and Big data nodes on movie rating data.
    knime > Examples > 10_Big_Data > 02_Spark_Executor > 10_Recommendation_Engine_w_Spark_Collaborative_Filtering
    1
  16. Workflow
    Lean Restocking Alert Signal: Training
    Backward feature elimination Random forest Decision tree
    +7
    This workflow implements an alarm system for bycicle restocking at Washington bike stations. The dataset is the bike dataset. Pro…
    knime > Examples > 50_Applications > 55_Bike_Restocking_Alert > 01_Bike_Restocking_Alert_Training_w_Feature_Selection
    1
  17. Workflow
    Keras Autoencoder for Fraud Detection Training
    Autoencoder Keras Neural network
    +16
    Partition numeric input data into a training, test, and validation set. Normalize the data into range [0,1]. Build a Keras autoen…
    knime > Examples > 50_Applications > 39_Fraud_Detection > 03_Keras_Autoencoder_for_Fraud_Detection_Training
    1
  18. Workflow
    Keras Autoencoder for Fraud Detection Deployment
    Autoencoder Keras Neural network
    +16
    Read Keras model. Read deployment data, which are normalized into range [0,1]. Apply the Keras model to the deployment data, calc…
    knime > Examples > 50_Applications > 39_Fraud_Detection > 04_Keras_Autoencoder_for_Fraud_Detection_Deployment
    1
  19. Workflow
    Market Basket Analysis: Apply Association Rules
    Retail Association rules Recommandation engine
    +9
    This workflow takes pre-built association rules and applies them to a new set of data 1. Read Association Rules and Product data …
    knime > Examples > 50_Applications > 16_MarketBasketAnalysis > 02_Apply_Association_Rules_for_MarketBasketAnalysis
    1
  20. Workflow
    Training a Churn Predictor
    Customer Intelligence CI Churn
    +2
    This workflow is an example of how to train a basic machine learning model for a churn prediction task. In this case we use a Dec…
    knime > Examples > 50_Applications > 18_Churn_Prediction > 01_Training_a_Churn_Predictor
    1