AI Extension Example Workflows

This space offers a curated collection of KNIME workflows, demonstrating practical applications in large language models, chat models, vector stores, and agents. It serves as a resource for understanding how to effectively utilise various AI capabilities within the KNIME environment for various tasks.

Last edited  Jul 19, 2023 9:06 AM

Beginners Space

The "KNIME Cheat Sheet: Building a KNIME Workflow for Beginners" is a great starting point for Beginners to start learning about KNIME. With this dedicated space, we showcase the usage of nodes mentioned in the Cheat Sheet to build simple workflows. The workflows are segregated into 5 categories: Read, Explore, Transform, Analyze and Deploy which is in line with the node categories defined in the Cheat Sheet. How to use this Space? Go to the "01_Read" folder and drag workflows to your KNIME Analytics Platform to learn reading data from the various file systems into KNIME, likewise go to the other folders and learn how to explore, transform, analyze data and then deploy using KNIME The Cheat Sheet "Building a KNIME Workflow for Beginners" is available for download at: knime.com/cheat-sheets If you want to give your acquired knowledge a test run, take a look at the Just KNIME It challenges at: knime.com/just-knime-it

Last edited  Mar 29, 2022 2:04 PM

Codeless Time Series Analysis with KNIME

This space contains the example workflows from the "Codeless Time Series Analysis with KNIME" book (published 2022).

Last edited  Sep 30, 2021 8:37 AM

Continuous Deployment for Data Science

This space contains the installation workflow for CDDS and example projects that can be used within CDDS. Documentation and guide for Continuous Deployment for Data Science (CDDS): http://docs.knime.com/latest/business_hub_cdds_guide/index.html

Last edited  Nov 14, 2022 6:20 PM

Digital Healthcare

KNIME solutions for classic problems on Digital Health

Last edited  Nov 24, 2021 2:23 PM

Education

This space offers all exercise workflows offered by the KNIME Evangelism team. Visit knime.com/courses and knime.com/educators to learn more of the free teaching materials that KNIME offers to learners and teachers!

Last edited  Jun 25, 2020 7:32 PM

Educators Alliance

This space contains materials (example workflows, assignments, etc.) for teaching with KNIME Analytics Platform.

Last edited  Feb 16, 2021 5:22 PM

Examples

Explore this space for workflows and verified components provided by us at KNIME to use as blueprints and building blocks for creating workflows to solve your own data science use cases.

Last edited  Jun 25, 2020 5:06 AM

Just KNIME It!

Solutions for the "Just KNIME It!" challenges, uploaded weekly to this Hub space.

Last edited  Nov 19, 2021 10:36 AM

KNIME Business Hub Admin Workflows

The workflows of this space support KNIME Business Hub (KBH) Administrators and heavy KBH users to clean up, monitor, and administrate their Business Hub installation. To execute these workflows, upload them to your KNIME Business Hub installation and run them Ad hoc or create deployments to be shared with other users.

Last edited  Jun 5, 2023 3:06 PM

KNIME Edge

This space contains workflows for initializing and utilizing a KNIME Edge cluster. Please contact our customer care team for information on getting started with KNIME Edge. KNIME Edge is a distributed, container-based platform that moves the consumption of models directly to where data is generated. Built on top of Kubernetes, KNIME Edge offers the ability to deploy workflows as highly available and scalable endpoints. This allows for high throughput and low latency while also decentralizing execution by deploying into data centers, manufacturing facilities, multiple cloud providers, and more. One or more KNIME Edge clusters can be remotely managed by leveraging KNIME Business Hub or KNIME Server. Using a few Data Apps on the Business Hub or on the KNIME Server’s WebPortal, a user can select and deploy workflows to any connected KNIME Edge clusters. Once a workflow is deployed, KNIME Edge creates locally consumable endpoints while managing execution, scaling, uptime, resiliency, and more to ensure model applications can scale seamlessly with demand.

Last edited  Feb 1, 2022 3:46 PM

KNIME for Finance

The "KNIME for Finance" space is for ready-to-use solutions that are designed to speed up analytics transformations within finance departments. These highly customizable solutions will help modernize financial processes within an organization through the use of self-service analytics.

Last edited  Jan 25, 2021 3:08 PM

KNIME for Spreadsheet Users

Find examples of the most common data manipulation tasks. They are recommended for beginners, particularly spreadsheet users, who are new to visual workflows.

Last edited  Feb 27, 2023 1:36 PM

KNIME Press

Last edited  Dec 19, 2023 8:49 AM

Life Sciences

Last edited  Jun 25, 2020 5:05 AM

Machine Learning and Marketing

This live repository contains example workflows of common data science problems in Marketing Analytics. The original task was explained in: F. Villarroel Ordenes & R. Silipo, “Machine learning for marketing on the KNIME Hub: The development of a live repository for marketing applications”, Journal of Business Research 137(1):393-410, DOI: 10.1016/j.jbusres.2021.08.036. Please cite this article, if you use any of the workflows in the repository.

Last edited  Apr 2, 2021 8:57 AM

Parameter Optimization Space

In this space we show both simple and complex workflows to learn how to fine-tune parameters for a generic classification model. Browse through those workflows to learn how to combine those nodes and components with any learner and predictor node which KNIME offers for ML classification.

Last edited  Oct 21, 2022 11:22 AM

Process Mining

This space offers a repository of example workflows for process mining. These examples vary by industry/domain, use case and nodes/components adopted.

Last edited  Oct 7, 2022 12:42 PM

Python Script Space

This Python Script Space aims to provide users with workflow examples on various use cases involving the Python Script node. Read more at: knime.com/blog/python-script-node-bundled-packages For detailed information check out the KNIME Docs at: docs.knime.com/latest/python_installation_guide The workflows are segregated into five folders as below: In 01_Getting_Started, the workflows will help you understand how to add/remove various input and output ports and access the input table or objects. In 02_Using_Bundled_Python_Packages, the workflows demonstrate the usage of bundled packages like NumPy, pandas, scikit-learn etc. In 03_Using_Custom_Python_Packages, the workflows demonstrate the usage of other python packages that are unavailable in the bundled environment and custom-defined python classes. In 04_Sharing_Python_Scripts_in_Components, the workflows showcase the creation of Scripted Components with Python. In 05_Jupyter_Notebook, the workflow demonstrates the usage of Jupyter Notebook inside the KNIME workflow

Last edited  Sep 27, 2022 9:47 AM

Server to Hub Migration

Workflows regarding the Migration from KNIME Server to KNIME Business or Communtiy Hub.

Last edited  May 8, 2024 4:01 PM

Sport Analytics

Last edited  Jun 19, 2024 10:56 AM

Supply Chain

This live repository contains example workflows of common data science problems in Supply Chain. Additionally this space contains examples of the verified component "Progress Tracker View".

Last edited  Aug 17, 2022 9:22 AM

Topic Modeling

In this space we show examples on how to use KNIME nodes and verified components for topic modeling.

Last edited  Jul 5, 2023 3:34 PM

Workflow Snippets

Find simple workflows for new users to KNIME demonstrating how to solve specific tasks or use specific nodes plus our favorite tips and tricks to help you along your learning path.

Last edited  Dec 9, 2021 12:48 PM

XAI Space

This space offers a collection of examples workflows for XAI. These workflows showcase how to use both: - Nodes from the KNIME Machine Learning Interpretability Extension: --> kni.me/e/IaoFfMScprMvBCY- - Model Interpretability Verified Components: --> hub.knime.com/knime/spaces/Examples/latest/~WMtQn1U91a-xzZY3/ These XAI examples can help you understand and interpret your machine learning model trained in KNIME. The workflows are divided into 2 main categories based on the ML Task : Classification and Regression. There are then also two sub-categories based on the type of training: AutoML and Custom Models. More infos on KNIME Blog: knime.com/blog/download-explainable-xai-solutions-hub KNIME Press Booklet download: knime.com/knimepress/explainable-ai

Last edited  Oct 21, 2022 11:21 AM