#DataApp

Paolo Tamagninipaolotamag
2023-10-11

⬆️🧵 Examples 🧵⬇️

Everyday new research papers are coming out!
on the keyword "KNIME" results via a data app!

Are you in academia? Join the
@KNIME
Educators Alliance at: knime.com/educators

Paolo Tamagninipaolotamag
2023-10-05

⬆️🧵 Examples 🧵⬇️

for asking specific questions on a just uploaded powered by and a

Read more on how to deploy a into a at: knime.com/blog/baking-ai-into-

Paolo Tamagninipaolotamag
2023-09-20

⬆️🧵 Examples 🧵⬇️

Annual Recurring Revenue (ARR) Analysis KPIs visualized and updated on demand via a data app

Workflow on the @KNIME Community Hub: hub.knime.com/-/spaces/-/lates

Paolo Tamagninipaolotamag
2023-08-23

⬆️🧵 Examples 🧵⬇️

cases visualized interactively in a data app

Read more on the blog "Following the Spread of Coronavirus" on @towardsdatascience

towardsdatascience.com/followi

Paolo Tamagninipaolotamag
2023-08-23

⬆️🧵 Examples 🧵⬇️

A data app to play tick-tack-toe with an trained with

Read more on @KNIME blog:
knime.com/blog/an-introduction-to-reinforcement-learning

Paolo Tamagninipaolotamag
2023-08-23

⬆️🧵 Examples 🧵⬇️

cases visualized interactively in a data app

Read more on the blog "Following the Spread of Coronavirus" on @towardsdatascience

towardsdatascience.com/following-the-spread-of-coronavirus-23626940c125

Paolo Tamagninipaolotamag
2023-08-23

⬆️🧵 Examples 🧵⬇️

A data app to run a game: guess the song based on the generated !

Find the workflow on KNIME Community Hub:
hub.knime.com/-/spaces/-/lates

Paolo Tamagninipaolotamag
2023-08-23

⬆️🧵 Examples 🧵⬇️

A data app to filter out columns dirty data to then generate charts: columns are selected based on interesting properties

Find the workflow on KNIME Community Hub:
hub.knime.com/-/spaces/-/lates

Paolo Tamagninipaolotamag
2023-08-23

⬆️🧵 Examples 🧵⬇️

A data app to control the component from the web browser.

Find the workflow on KNIME Community Hub:
hub.knime.com/-/spaces/-/lates

Paolo Tamagninipaolotamag
2023-08-23

⬆️🧵 Examples 🧵⬇️

A data app to browse data of different countries.

Find the workflow on KNIME Community Hub:
hub.knime.com/-/spaces/-/lates

Paolo Tamagninipaolotamag
2023-08-18

⬆️🧵 @KNIME Examples 🧵⬇️

This offers a guided experience to automatically train models on custom data: upload, select target, select features, models and setting and export results!

Learn more on @KNIME Blog:
knime.com/blog/how-to-automate-machine-learning

Paolo Tamagninipaolotamag
2023-08-18

⬆️🧵 @KNIME Examples 🧵⬇️

API can be inspected via this data app given a time window, a geographical location and users/session setting. can help you provide a custom experience for your use cases.

Check the workflow at:
hub.knime.com/-/spaces/-/latest/~R8fsXF-q1tBk5WeB/

Paolo Tamagninipaolotamag
2023-08-18

⬆️🧵 @KNIME Examples 🧵⬇️

Continuous Deployment for Data Science (CDDS) offers a framework to deploy and maintaing any data science workflow! This data app offers a control panel to the data scientist to submit project for validation and production.

Learn more at:
knime.com/solutions/knime-continuous-deployment-data-science

Paolo Tamagninipaolotamag
2023-08-18

⬆️🧵 @KNIME Examples 🧵⬇️

The local explanation view lets you inspect what features where most responsible for a single prediction. It also provides counterfactuals for inspection.

Learn more on components on @KNIME Press:
knime.com/knimepress/explainable-ai

Paolo Tamagninipaolotamag
2023-08-18

⬆️🧵 @KNIME Examples 🧵⬇️

Inspecting global feature importance of a machine learning model helps getting an overview of which features are used. Different techniques are provided by this data app.

Learn more on components on @KNIME Press:
knime.com/knimepress/explainable-ai

Paolo Tamagninipaolotamag
2023-08-18

⬆️🧵 @KNIME Examples 🧵⬇️

Parameter optimization can be performed too from a web browser. This data app let you customize the settings of your parameter search and generate results to inspect how the optimization was doing iteration by iteration.

Read more on @KNIME Blog:
knime.com/blog/simplify-parameter-optimization-codeless

Paolo Tamagninipaolotamag
2023-08-18

⬆️🧵 @KNIME Examples 🧵⬇️

The AutoML (Regression) component trains a variety of model. A data app is shipped with the component to browse and inspect the resulting automatically trained models!

Find the verified component at: hub.knime.com/-/spaces/-/latest/~5kzQcySUa8oukv0Y/

Paolo Tamagninipaolotamag
2023-08-18

⬆️🧵 @KNIME Examples 🧵⬇️

Testing your model manually can be handy both for debugging or understanding it. The model simulation view lets you do just that both for regression and classification models!

Learn more on components on @KNIME Press:
knime.com/knimepress/explainable-ai

Paolo Tamagninipaolotamag
2023-08-18

⬆️🧵 @KNIME Examples 🧵⬇️

is a big deal in @KNIME Berlin office! We use a data app to track the scores on a leaderboard, submit new games, inspect player stats and generate some LLM gibberish text. How fun!

Join ! knime.com/careers

Paolo Tamagninipaolotamag
2023-08-18

⬆️🧵 @KNIME Examples 🧵⬇️

Upload a CV, get a summary via API!
approach to build a to manage the before and after the is applied.

Learn more on the KNIME Extension: hub.knime.com/-/spaces/-/lates

Client Info

Server: https://mastodon.social
Version: 2025.04
Repository: https://github.com/cyevgeniy/lmst