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Machine Learning Meta Collection (with KNIME)

Machine Learning Meta Collection (with KNIME)

This meta collection is about machine learning. It contains links to some examples demonstrating several types of machine learning mosttly with KNIME and also some links how to learn machine learning (again mostly witth KNIME). It is not a complete collection of ML methods and algorithms and far from answering all questions or covering all topics - more like a quick practical overview of some aspects; and always with a focus on Mnimal Viable Examples you could try at home. Please note these examples do not substitute for a deeper understanding of your business problems and the various -statistical- implications to consider when using such models - in other words: terms and conditions *do* apply.

--------------- Learning Machine Learning (with KNIME) ---------

How to learn machine learning with KNIME
https://forum.knime.com/t/knime-based-machine-learning-course/21876/2?u=mlauber71

[L1-DS] - KNIME Analytics Platform for Data Scientists: Basics
Lesson 4. Machine Learning & Data Export
https://www.knime.com/self-paced-course/l1-ds-knime-analytics-platform-for-data-scientists-basics/lesson4?u=mlauber71

-----------------------------------------------------------------

Links to types of prediction models
https://forum.knime.com/t/how-to-find-the-optimal-process-parameter-based-on-quality-defects/20846/6?u=mlauber71

-----
1) Models for binary classsifications - 0/1 or Yes/No Targets
https://forum.knime.com/t/looking-for-options-to-evaluate-a-decision-tree/11384/2?u=mlauber71
 
Understand metrics like AUC and Gini (and use H2O.ai)
https://forum.knime.com/t/random-forest-model-not-working/12738/3?u=mlauber71
https://forum.knime.com/t/help-choosing-analytics-algorithm/11404/3?u=mlauber71

11 Important Model Evaluation Metrics for Machine Learning Everyone should know
https://www.analyticsvidhya.com/blog/2019/08/11-important-model-evaluation-error-metrics/


-----
2) Model for Multiclass Targets (and explanation of Log Loss statistics)
https://forum.knime.com/t/any-advice-to-improve-the-performance-of-a-classification-model/12801/10?u=mlauber71
https://forum.knime.com/t/metrics-in-multiclass-classification/11193/3?u=mlauber71

Score Documents with multiple Classes?
https://forum.knime.com/t/urgent-what-is-wrong-with-my-decision-tree-predictor-for-new-data/13292/10?u=mlauber71

-----
3) Regression models (numeric Target)
https://forum.knime.com/t/predictive-analytics-for-sales/12858/3?u=mlauber71
https://forum.knime.com/t/forecasting-sales-per-customer-for-the-next-360-days/13221/4?u=mlauber71
https://forum.knime.com/t/evaluate-a-linear-regression-model/13305/2?u=mlauber71

https://forum.knime.com/t/how-to-identify-the-top-100-features-selected-from-mlp-model/11371/2?u=mlauber71
 
Regression collection (Time Series)
https://forum.knime.com/t/prediction-based-on-multi-variables/20184/5?u=mlauber71

predict how many future visitors a restaurant will receive (with H2O.ai)
https://www.knime.com/blog/solving-a-kaggle-challenge-using-the-combined-power-of-knime-analytics-platform-h2o?u=mlauber71

------------------------------------------------------------

PMML Models with numeric scores
https://forum.knime.com/t/export-pmml-that-outputs-class-probabilities/13244/2?u=mlauber71

-----------------------------------------------------------------
Data preparation steps

[preparation] Techniques for Dimensionality Reduction
https://hub.knime.com/knime/spaces/Examples/latest/04_Analytics/01_Preprocessing/02_Techniques_for_Dimensionality_Reduction/02_Techniques_for_Dimensionality_Reduction~7PBv1kGifxCng2qo

[preparation] Three New Techniques for Data Dimensionality Reduction in Machine Learning
https://www.knime.com/blog/three-new-techniques-for-data-dimensionality-reduction-in-machine-learning

[preparation] use R's vtreat to automatically prepare data fo classification and regression tasks
https://forum.knime.com/t/is-artificial-intelligence-used-for-data-cleansing-techniques-used-by-knime/36209/6?u=mlauber71

[preparation] Spark Label Encoding, remove highly correlated variables - prepare the data in local Big Data environment
https://hub.knime.com/mlauber71/spaces/Public/latest/kn_example_bigdata_h2o_automl_spark/s_401_spark_label_encoder~mF4g6HTMX7J4m27Q

prepare the preparation of data in a big data environment
- label encode string variables
- transform numbers into Double format (Spark ML likes that)
- remove highly correlated data
- remove NaN variables
- remove continous variables
- optional: normalize the data

-----------------------------------------------------------------
How to handle missing values

Basic missing value handling
https://hub.knime.com/knime/spaces/Examples/latest/02_ETL_Data_Manipulation/04_Transformation/01_Handling_Missing_Values

some more advanced approaches to missing values
https://hub.knime.com/knime/spaces/Education/latest/Courses/L4-ML%20Introduction%20to%20Machine%20Learning%20Algorithms/Session_4/02_Solutions/02_Missing_Value_Handling_solution

Multipe Imputation for Missing Values
https://hub.knime.com/kathrin/spaces/Missing%20Value%20Imputation/latest/Mulitple%20Imputation%20for%20Missing%20Values

Comparing Missing Value Handling Methods
https://hub.knime.com/kathrin/spaces/Missing%20Value%20Imputation/latest/Comparing%20Missing%20Value%20Handling%20Methods

Employ R's Amelia package to replace missing values
https://hub.knime.com/mlauber71/spaces/Public/latest/kn_example_r_amelia/m_001_missing_values_amelia

-----------------------------------------------------------------

about unbalanced Targets
https://forum.knime.com/t/xgboost-predictor/23960/5?u=mlauber71

about unbalanced data and evaluation metrics (AUCPR)
https://forum.knime.com/t/problem-with-unbalanced-data-with-examples-attached/26227/4?u=mlauber71

another thread about how to handle imbalanced data
https://forum.knime.com/t/knime-fraud-detection-autoencoder/28859/17?u=mlauber71


--------------- KNIME and H2O.ai ----------

H2O.ai models and KNIME in general
https://www.knime.com/nodeguide/analytics/h2o-machine-learning?u=mlauber71

simple example how to use H2O.ai models in a Big Data environment
https://hub.knime.com/mlauber71/spaces/Public/latest/kn_example_h2o_sparkling_water?u=mlauber71

H2O.ai AutoML in KNIME for classification problems
https://forum.knime.com/t/h2o-ai-automl-in-knime-for-classification-problems/20923?u=mlauber71

H2O.ai AutoML in KNIME for regression problems
https://forum.knime.com/t/h2o-ai-automl-in-knime-for-regression-problems/20924?u=mlauber71


„Sparkling Predictions and Encoded Labels – Developing and Deploying Predictive Models on a Big Data Cluster with KNIME, Spark and H2O.ai“
(talk in German, slides in English)
https://www.youtube.com/watch?v=k8MsxzwEVrk&t=4335s

--------------- KNIME and Python ----------

use Python and KNIME to make a random forest (quick basic example)
https://hub.knime.com/mlauber71/spaces/Public/latest/kn_example_python_iris?u=mlauber71


Python Installation (the very short story)
https://forum.knime.com/t/problem-with-setting-a-python-deep-learning-environment/19477/2?u=mlauber71
https://forum.knime.com/t/installing-a-new-library-in-python/25365/4?u=mlauber71

Python KNIME official installation
https://docs.knime.com/2020-07/python_installation_guide/index.html?u=mlauber71

Python and Deep Learning
https://docs.knime.com/latest/deep_learning_installation_guide/index.html?u=mlauber71

Python and Anaconda versions / Python and Keras
https://forum.knime.com/t/python-extension-not-recognizing-anaconda-environment-in-knime-3-7/12978/3?u=mlauber71
https://forum.knime.com/t/python-extension-not-recognizing-anaconda-environment-in-knime-3-7/12978/9?u=mlauber71


--------------- Special ----------

Rule Induction with Weka Rule Nodes and Yacaree Associator
https://hub.knime.com/mlauber71/spaces/Public/latest/kn_example_rule_induction_weka_hotspot_and_yacaree_rules?u=mlauber71

Not strictly a KNIME thing but very helpful books and blogs about ML and Python
https://machinelearningmastery.com/

Clustering Algorithms (small collection in KNIME)
https://forum.knime.com/t/ml-techniques-which-one-can-i-use-to-predict-sales-in-a-particular-country/28783/5?u=mlauber71

Machine Learning Meta Collection (with KNIME)This meta collection is about machine learning. It contains links to some examples demonstrating several types of machine learning mosttly with KNIME and also some links how to learn machine learning (again mostly witth KNIME). It isnot a complete collection of ML methods and algorithms and far from answering all questions or covering all topics - more like a quick practical overview of some aspects; and always with a focus on Mnimal Viable Examples you could try athome. Please note these examples do not substitute for a deeper understanding of your business problems and the various -statistical- implications to consider when using such models - in other words: terms and conditions *do* apply.--------------- Learning Machine Learning (with KNIME) ---------How to learn machine learning with KNIMEhttps://forum.knime.com/t/knime-based-machine-learning-course/21876/2?u=mlauber71[L1-DS] - KNIME Analytics Platform for Data Scientists: BasicsLesson 4. Machine Learning & Data Exporthttps://www.knime.com/self-paced-course/l1-ds-knime-analytics-platform-for-data-scientists-basics/lesson4?u=mlauber71-----------------------------------------------------------------Links to types of prediction modelshttps://forum.knime.com/t/how-to-find-the-optimal-process-parameter-based-on-quality-defects/20846/6?u=mlauber71-----1) Models for binary classsifications - 0/1 or Yes/No Targetshttps://forum.knime.com/t/looking-for-options-to-evaluate-a-decision-tree/11384/2?u=mlauber71 Understand metrics like AUC and Gini (and use H2O.ai)https://forum.knime.com/t/random-forest-model-not-working/12738/3?u=mlauber71https://forum.knime.com/t/help-choosing-analytics-algorithm/11404/3?u=mlauber7111 Important Model Evaluation Metrics for Machine Learning Everyone should knowhttps://www.analyticsvidhya.com/blog/2019/08/11-important-model-evaluation-error-metrics/-----2) Model for Multiclass Targets (and explanation of Log Loss statistics)https://forum.knime.com/t/any-advice-to-improve-the-performance-of-a-classification-model/12801/10?u=mlauber71https://forum.knime.com/t/metrics-in-multiclass-classification/11193/3?u=mlauber71Score Documents with multiple Classes?https://forum.knime.com/t/urgent-what-is-wrong-with-my-decision-tree-predictor-for-new-data/13292/10?u=mlauber71-----3) Regression models (numeric Target)https://forum.knime.com/t/predictive-analytics-for-sales/12858/3?u=mlauber71https://forum.knime.com/t/forecasting-sales-per-customer-for-the-next-360-days/13221/4?u=mlauber71https://forum.knime.com/t/evaluate-a-linear-regression-model/13305/2?u=mlauber71https://forum.knime.com/t/how-to-identify-the-top-100-features-selected-from-mlp-model/11371/2?u=mlauber71 Regression collection (Time Series)https://forum.knime.com/t/prediction-based-on-multi-variables/20184/5?u=mlauber71predict how many future visitors a restaurant will receive (with H2O.ai)https://www.knime.com/blog/solving-a-kaggle-challenge-using-the-combined-power-of-knime-analytics-platform-h2o?u=mlauber71------------------------------------------------------------PMML Models with numeric scoreshttps://forum.knime.com/t/export-pmml-that-outputs-class-probabilities/13244/2?u=mlauber71-----------------------------------------------------------------Data preparation steps[preparation] Techniques for Dimensionality Reductionhttps://hub.knime.com/knime/spaces/Examples/latest/04_Analytics/01_Preprocessing/02_Techniques_for_Dimensionality_Reduction/02_Techniques_for_Dimensionality_Reduction~7PBv1kGifxCng2qo[preparation] Three New Techniques for Data Dimensionality Reduction in Machine Learninghttps://www.knime.com/blog/three-new-techniques-for-data-dimensionality-reduction-in-machine-learning[preparation] use R's vtreat to automatically prepare data fo classification and regression taskshttps://forum.knime.com/t/is-artificial-intelligence-used-for-data-cleansing-techniques-used-by-knime/36209/6?u=mlauber71[preparation] Spark Label Encoding, remove highly correlated variables - prepare the data in local Big Data environmenthttps://hub.knime.com/mlauber71/spaces/Public/latest/kn_example_bigdata_h2o_automl_spark/s_401_spark_label_encoder~mF4g6HTMX7J4m27Qprepare the preparation of data in a big data environment - label encode string variables - transform numbers into Double format (Spark ML likes that) - remove highly correlated data - remove NaN variables - remove continous variables - optional: normalize the data-----------------------------------------------------------------How to handle missing valuesBasic missing value handlinghttps://hub.knime.com/knime/spaces/Examples/latest/02_ETL_Data_Manipulation/04_Transformation/01_Handling_Missing_Valuessome more advanced approaches to missing valueshttps://hub.knime.com/knime/spaces/Education/latest/Courses/L4-ML%20Introduction%20to%20Machine%20Learning%20Algorithms/Session_4/02_Solutions/02_Missing_Value_Handling_solutionMultipe Imputation for Missing Valueshttps://hub.knime.com/kathrin/spaces/Missing%20Value%20Imputation/latest/Mulitple%20Imputation%20for%20Missing%20ValuesComparing Missing Value Handling Methodshttps://hub.knime.com/kathrin/spaces/Missing%20Value%20Imputation/latest/Comparing%20Missing%20Value%20Handling%20MethodsEmploy R's Amelia package to replace missing valueshttps://hub.knime.com/mlauber71/spaces/Public/latest/kn_example_r_amelia/m_001_missing_values_amelia-----------------------------------------------------------------about unbalanced Targetshttps://forum.knime.com/t/xgboost-predictor/23960/5?u=mlauber71about unbalanced data and evaluation metrics (AUCPR)https://forum.knime.com/t/problem-with-unbalanced-data-with-examples-attached/26227/4?u=mlauber71another thread about how to handle imbalanced datahttps://forum.knime.com/t/knime-fraud-detection-autoencoder/28859/17?u=mlauber71--------------- KNIME and H2O.ai ----------H2O.ai models and KNIME in generalhttps://www.knime.com/nodeguide/analytics/h2o-machine-learning?u=mlauber71simple example how to use H2O.ai models in a Big Data environmenthttps://hub.knime.com/mlauber71/spaces/Public/latest/kn_example_h2o_sparkling_water?u=mlauber71H2O.ai AutoML in KNIME for classification problemshttps://forum.knime.com/t/h2o-ai-automl-in-knime-for-classification-problems/20923?u=mlauber71H2O.ai AutoML in KNIME for regression problemshttps://forum.knime.com/t/h2o-ai-automl-in-knime-for-regression-problems/20924?u=mlauber71„Sparkling Predictions and Encoded Labels – Developing and Deploying Predictive Models on a Big Data Cluster with KNIME, Spark and H2O.ai“(talk in German, slides in English)https://www.youtube.com/watch?v=k8MsxzwEVrk&t=4335s--------------- KNIME and Python ----------use Python and KNIME to make a random forest (quick basic example)https://hub.knime.com/mlauber71/spaces/Public/latest/kn_example_python_iris?u=mlauber71Python Installation (the very short story)https://forum.knime.com/t/problem-with-setting-a-python-deep-learning-environment/19477/2?u=mlauber71https://forum.knime.com/t/installing-a-new-library-in-python/25365/4?u=mlauber71Python KNIME official installationhttps://docs.knime.com/2020-07/python_installation_guide/index.html?u=mlauber71Python and Deep Learninghttps://docs.knime.com/latest/deep_learning_installation_guide/index.html?u=mlauber71Python and Anaconda versions / Python and Kerashttps://forum.knime.com/t/python-extension-not-recognizing-anaconda-environment-in-knime-3-7/12978/3?u=mlauber71https://forum.knime.com/t/python-extension-not-recognizing-anaconda-environment-in-knime-3-7/12978/9?u=mlauber71--------------- Special ----------Rule Induction with Weka Rule Nodes and Yacaree Associatorhttps://hub.knime.com/mlauber71/spaces/Public/latest/kn_example_rule_induction_weka_hotspot_and_yacaree_rules?u=mlauber71Not strictly a KNIME thing but very helpful books and blogs about ML and Pythonhttps://machinelearningmastery.com/Clustering Algorithms (small collection in KNIME)https://forum.knime.com/t/ml-techniques-which-one-can-i-use-to-predict-sales-in-a-particular-country/28783/5?u=mlauber71 Start to Learn KNIME - a short Collectionhttps://medium.com/p/d4b16c9616adVideo: L2 for KNIME Version 4 (also covering the basics of Machine-Learning)https://www.youtube.com/playlist?list=PLz3mQ6OlTI0Yd4UtwQ7x77Hoh5MSuN66MMedium: About Machine-Learning — How it Fails and Succeedshttps://medium.com/p/9f3ab7cb9b00Medium: KNIME — Machine Learning and Artificial Intelligence— A Collectionhttps://medium.com/p/12e0f7d83b50 Machine Learning Meta Collection (with KNIME)This meta collection is about machine learning. It contains links to some examples demonstrating several types of machine learning mosttly with KNIME and also some links how to learn machine learning (again mostly witth KNIME). It isnot a complete collection of ML methods and algorithms and far from answering all questions or covering all topics - more like a quick practical overview of some aspects; and always with a focus on Mnimal Viable Examples you could try athome. Please note these examples do not substitute for a deeper understanding of your business problems and the various -statistical- implications to consider when using such models - in other words: terms and conditions *do* apply.--------------- Learning Machine Learning (with KNIME) ---------How to learn machine learning with KNIMEhttps://forum.knime.com/t/knime-based-machine-learning-course/21876/2?u=mlauber71[L1-DS] - KNIME Analytics Platform for Data Scientists: BasicsLesson 4. Machine Learning & Data Exporthttps://www.knime.com/self-paced-course/l1-ds-knime-analytics-platform-for-data-scientists-basics/lesson4?u=mlauber71-----------------------------------------------------------------Links to types of prediction modelshttps://forum.knime.com/t/how-to-find-the-optimal-process-parameter-based-on-quality-defects/20846/6?u=mlauber71-----1) Models for binary classsifications - 0/1 or Yes/No Targetshttps://forum.knime.com/t/looking-for-options-to-evaluate-a-decision-tree/11384/2?u=mlauber71 Understand metrics like AUC and Gini (and use H2O.ai)https://forum.knime.com/t/random-forest-model-not-working/12738/3?u=mlauber71https://forum.knime.com/t/help-choosing-analytics-algorithm/11404/3?u=mlauber7111 Important Model Evaluation Metrics for Machine Learning Everyone should knowhttps://www.analyticsvidhya.com/blog/2019/08/11-important-model-evaluation-error-metrics/-----2) Model for Multiclass Targets (and explanation of Log Loss statistics)https://forum.knime.com/t/any-advice-to-improve-the-performance-of-a-classification-model/12801/10?u=mlauber71https://forum.knime.com/t/metrics-in-multiclass-classification/11193/3?u=mlauber71Score Documents with multiple Classes?https://forum.knime.com/t/urgent-what-is-wrong-with-my-decision-tree-predictor-for-new-data/13292/10?u=mlauber71-----3) Regression models (numeric Target)https://forum.knime.com/t/predictive-analytics-for-sales/12858/3?u=mlauber71https://forum.knime.com/t/forecasting-sales-per-customer-for-the-next-360-days/13221/4?u=mlauber71https://forum.knime.com/t/evaluate-a-linear-regression-model/13305/2?u=mlauber71https://forum.knime.com/t/how-to-identify-the-top-100-features-selected-from-mlp-model/11371/2?u=mlauber71 Regression collection (Time Series)https://forum.knime.com/t/prediction-based-on-multi-variables/20184/5?u=mlauber71predict how many future visitors a restaurant will receive (with H2O.ai)https://www.knime.com/blog/solving-a-kaggle-challenge-using-the-combined-power-of-knime-analytics-platform-h2o?u=mlauber71------------------------------------------------------------PMML Models with numeric scoreshttps://forum.knime.com/t/export-pmml-that-outputs-class-probabilities/13244/2?u=mlauber71-----------------------------------------------------------------Data preparation steps[preparation] Techniques for Dimensionality Reductionhttps://hub.knime.com/knime/spaces/Examples/latest/04_Analytics/01_Preprocessing/02_Techniques_for_Dimensionality_Reduction/02_Techniques_for_Dimensionality_Reduction~7PBv1kGifxCng2qo[preparation] Three New Techniques for Data Dimensionality Reduction in Machine Learninghttps://www.knime.com/blog/three-new-techniques-for-data-dimensionality-reduction-in-machine-learning[preparation] use R's vtreat to automatically prepare data fo classification and regression taskshttps://forum.knime.com/t/is-artificial-intelligence-used-for-data-cleansing-techniques-used-by-knime/36209/6?u=mlauber71[preparation] Spark Label Encoding, remove highly correlated variables - prepare the data in local Big Data environmenthttps://hub.knime.com/mlauber71/spaces/Public/latest/kn_example_bigdata_h2o_automl_spark/s_401_spark_label_encoder~mF4g6HTMX7J4m27Qprepare the preparation of data in a big data environment - label encode string variables - transform numbers into Double format (Spark ML likes that) - remove highly correlated data - remove NaN variables - remove continous variables - optional: normalize the data-----------------------------------------------------------------How to handle missing valuesBasic missing value handlinghttps://hub.knime.com/knime/spaces/Examples/latest/02_ETL_Data_Manipulation/04_Transformation/01_Handling_Missing_Valuessome more advanced approaches to missing valueshttps://hub.knime.com/knime/spaces/Education/latest/Courses/L4-ML%20Introduction%20to%20Machine%20Learning%20Algorithms/Session_4/02_Solutions/02_Missing_Value_Handling_solutionMultipe Imputation for Missing Valueshttps://hub.knime.com/kathrin/spaces/Missing%20Value%20Imputation/latest/Mulitple%20Imputation%20for%20Missing%20ValuesComparing Missing Value Handling Methodshttps://hub.knime.com/kathrin/spaces/Missing%20Value%20Imputation/latest/Comparing%20Missing%20Value%20Handling%20MethodsEmploy R's Amelia package to replace missing valueshttps://hub.knime.com/mlauber71/spaces/Public/latest/kn_example_r_amelia/m_001_missing_values_amelia-----------------------------------------------------------------about unbalanced Targetshttps://forum.knime.com/t/xgboost-predictor/23960/5?u=mlauber71about unbalanced data and evaluation metrics (AUCPR)https://forum.knime.com/t/problem-with-unbalanced-data-with-examples-attached/26227/4?u=mlauber71another thread about how to handle imbalanced datahttps://forum.knime.com/t/knime-fraud-detection-autoencoder/28859/17?u=mlauber71--------------- KNIME and H2O.ai ----------H2O.ai models and KNIME in generalhttps://www.knime.com/nodeguide/analytics/h2o-machine-learning?u=mlauber71simple example how to use H2O.ai models in a Big Data environmenthttps://hub.knime.com/mlauber71/spaces/Public/latest/kn_example_h2o_sparkling_water?u=mlauber71H2O.ai AutoML in KNIME for classification problemshttps://forum.knime.com/t/h2o-ai-automl-in-knime-for-classification-problems/20923?u=mlauber71H2O.ai AutoML in KNIME for regression problemshttps://forum.knime.com/t/h2o-ai-automl-in-knime-for-regression-problems/20924?u=mlauber71„Sparkling Predictions and Encoded Labels – Developing and Deploying Predictive Models on a Big Data Cluster with KNIME, Spark and H2O.ai“(talk in German, slides in English)https://www.youtube.com/watch?v=k8MsxzwEVrk&t=4335s--------------- KNIME and Python ----------use Python and KNIME to make a random forest (quick basic example)https://hub.knime.com/mlauber71/spaces/Public/latest/kn_example_python_iris?u=mlauber71Python Installation (the very short story)https://forum.knime.com/t/problem-with-setting-a-python-deep-learning-environment/19477/2?u=mlauber71https://forum.knime.com/t/installing-a-new-library-in-python/25365/4?u=mlauber71Python KNIME official installationhttps://docs.knime.com/2020-07/python_installation_guide/index.html?u=mlauber71Python and Deep Learninghttps://docs.knime.com/latest/deep_learning_installation_guide/index.html?u=mlauber71Python and Anaconda versions / Python and Kerashttps://forum.knime.com/t/python-extension-not-recognizing-anaconda-environment-in-knime-3-7/12978/3?u=mlauber71https://forum.knime.com/t/python-extension-not-recognizing-anaconda-environment-in-knime-3-7/12978/9?u=mlauber71--------------- Special ----------Rule Induction with Weka Rule Nodes and Yacaree Associatorhttps://hub.knime.com/mlauber71/spaces/Public/latest/kn_example_rule_induction_weka_hotspot_and_yacaree_rules?u=mlauber71Not strictly a KNIME thing but very helpful books and blogs about ML and Pythonhttps://machinelearningmastery.com/Clustering Algorithms (small collection in KNIME)https://forum.knime.com/t/ml-techniques-which-one-can-i-use-to-predict-sales-in-a-particular-country/28783/5?u=mlauber71 Start to Learn KNIME - a short Collectionhttps://medium.com/p/d4b16c9616adVideo: L2 for KNIME Version 4 (also covering the basics of Machine-Learning)https://www.youtube.com/playlist?list=PLz3mQ6OlTI0Yd4UtwQ7x77Hoh5MSuN66MMedium: About Machine-Learning — How it Fails and Succeedshttps://medium.com/p/9f3ab7cb9b00Medium: KNIME — Machine Learning and Artificial Intelligence— A Collectionhttps://medium.com/p/12e0f7d83b50

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To use this workflow in KNIME, download it from the below URL and open it in KNIME:

Download Workflow
Created by: m_lauber
Created at: 2020-09-08
On NodePit since: 2020-09-09
Last update: 2024-05-17
Created with KNIME version: v4.7.8
Tags: knimemachinelearningmodelscorepmmlh2oh2o.aiwekaimbalancedloglossaucaucprmojo

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