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TheGuideBook
GIDS Academia Exercise Classification Machine learning
+3
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    Workflow
    Clustering with k-Means
    Clustering K-Means Machine learning
    +3
    This workflow performs clustering of the iris dataset using k-Means. Two workflows: one to build the k-Means prototypes (top) and…
    knime > Academic Alliance > Guide to Intelligent Data Science > Example Workflows > Chapter7 > 02_kMeans
    5
  2. Go to item
    Workflow
    Classification of the iris data using kNN
    TheGuideBook KNN K Nearest Neighbor
    +2
    This workflow solves a classification problem on the iris dataset using the k-Nearest Neighbor (kNN) algorithm.
    knime > Academic Alliance > Guide to Intelligent Data Science > Example Workflows > Chapter9 > 01_kNN
    2
  3. Go to item
    Workflow
    Clustering with DBSCAN
    Clustering Machine learning Data mining
    +3
    This workflow performs clustering of the iris dataset using DBSCAN. Notice the Numeric Distances node to feed the DBSCAN node wit…
    knime > Academic Alliance > Guide to Intelligent Data Science > Example Workflows > Chapter7 > 03_DBSCAN
    2
  4. Go to item
    Workflow
    Hierarchical Clustering
    Clustering Machine learning Data mining
    +3
    This workflow clusters the iris dataset using Hierarchical Clustering
    jjmie > Public > 01_HierarchicalClustering
    1
  5. Go to item
    Workflow
    Decision Tree
    TheGuideBook Decision Tree Classification
    +1
    Using the adult dataset, this workflow performs binary classification (income > or < 50K) using a Decision Tree. The target is th…
    knime > Academic Alliance > Guide to Intelligent Data Science > Example Workflows > Chapter8 > 01_DecisionTree
    1
  6. Go to item
    Workflow
    Hierarchical Clustering
    Clustering Machine learning Data mining
    +3
    This workflow clusters the iris dataset using Hierarchical Clustering
    knime > Academic Alliance > Guide to Intelligent Data Science > Example Workflows > Chapter7 > 01_HierarchicalClustering
    1
  7. Go to item
    Workflow
    02_Deployment
    GIDS Exercise Academia
    +4
    In this exercise you will use a previously trained neural network to predict some unseen data.
    knime > Academic Alliance > Guide to Intelligent Data Science > Exercises > Chapter9_Neural_Networks > Solution > 02_Deployment_Solution
    0
  8. Go to item
    Workflow
    Hierarchical Clustering
    Clustering Machine learning Data mining
    +3
    This workflow clusters the iris dataset using Hierarchical Clustering
    emilio_s > Public Exercises > DL Italia > Lesson 3 > 5) 01_HierarchicalClustering
    0
  9. Go to item
    Workflow
    SVM on iris dataset
    TheGuideBook SVM Classification
    +2
    This workflow solves a classification problem on the iris dataset using Support Vector Machines (SVM).
    jessi > Public > 03_SVM
    0
  10. Go to item
    Workflow
    Introduction
    GIDS Exercise Academia
    +1
    Exercise to perform basic operations in KNIME: - Read data - Filter rows - Filter columns - Write and plot data
    knime > Academic Alliance > Guide to Intelligent Data Science > Exercises > Chapter1_Introduction > Introduction_Exercise
    0
  11. Go to item
    Workflow
    02_Deployment_LSTM_Solution
    GIDS Exercise Academia
    +3
    Use a trained LSTM model to perform free text generation. - Predict the next character given a starting sequence - Use different …
    knime > Academic Alliance > Guide to Intelligent Data Science > Exercises > Chapter9_Deep_Learning_LSTM > 02_Deployment_LSTM_Solution
    0
  12. Go to item
    Workflow
    02_Deployment_LSTM_Exercise
    GIDS Exercise Academia
    +3
    Use a trained LSTM model to perform free text generation. - Predict the next character given a starting sequence - Use different …
    knime > Academic Alliance > Guide to Intelligent Data Science > Exercises > Chapter9_Deep_Learning_LSTM > 02_Deployment_LSTM_Exercise
    0
  13. Go to item
    Workflow
    Logistic Regression
    Logistic regression Classification Education
    +4
    Logistic Regression: predict wine color. - Normalize numerical columns - Partition the dataset into train and test set - Train a …
    knime > Academic Alliance > Guide to Intelligent Data Science > Exercises > Chapter8_Regression > Logistic_Regression_Solution
    0
  14. Go to item
    Workflow
    SVM Exercise with Parameter Optimization
    SVM Support vector machine Classification
    +4
    Exercise for SVM. Classification of 2D silhouette attributes with SVM classifier. Oprimize the c parameter for the margin hardnes…
    knime > Academic Alliance > Guide to Intelligent Data Science > Exercises > Chapter9_SVM > SVM_Exercise
    0
  15. Go to item
    Workflow
    Decision Tree
    Classification Education Decision tree
    +4
    Decision Tree: binary classification of house ranking (high/low rank). - Create target column - Filter unnecessary columns - Spli…
    knime > Academic Alliance > Guide to Intelligent Data Science > Exercises > Chapter8_Decision_and_Regression_Trees > Decision_Tree_Exercise
    0
  16. Go to item
    Workflow
    Dimensionality Reduction with PCA and t-SNE
    TheGuideBook Scatter plot PCA
    +4
    This workflow applyes two dimensionality reduction techniques: -PCA -t-SNE to reduce the dataset dimensions from three to two fea…
    knime > Academic Alliance > Guide to Intelligent Data Science > Example Workflows > Chapter4 > 02_PCA_t-SNE
    0
  17. Go to item
    Workflow
    Deployment to a Dashboard
    TheGuideBook Deployment Dashboard
    +1
    This deployment workflow builds a simple dashboard. Reads a pre-trained decision tree model and applies it to new data to predict…
    schramm > New space > 01_Deploy_on_Dashboard
    0
  18. Go to item
    Workflow
    02_Deployment
    GIDS Exercise Academia
    +4
    In this exercise you will use a previously trained neural network to predict some unseen data.
    knime > Academic Alliance > Guide to Intelligent Data Science > Exercises > Chapter9_Neural_Networks > Exercise > 02_Deployment
    0
  19. Go to item
    Workflow
    Regression Tree
    Regression Machine learning Education
    +4
    Regression Tree: predict house price. - Partition data into training and test set - Train a regression tree model - Apply the tra…
    knime > Academic Alliance > Guide to Intelligent Data Science > Exercises > Chapter8_Decision_and_Regression_Trees > Regression_Tree_Exercise
    0
  20. Go to item
    Workflow
    Numeric_Scorer
    GIDS Exercise Academia
    +2
    Numeric scorer: compare performance of two regression models
    knime > Academic Alliance > Guide to Intelligent Data Science > Exercises > Chapter5_Principles_of_Modeling > Numeric_Scorer_Solution
    0

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