KNIME Integrations

Integrate Big Data, Machine Learning, AI, Scripting, and more.
KNIME Integrations
KNIME Integrations

Open source integrations for KNIME Analytics Platform (also developed and maintained by KNIME), provide seamless access to large open source projects such as Keras for deep learning, H2O for high performance machine learning, Apache Spark for big data processing, Python and R for scripting, and more.

Big Data
Big Data

Import, export, and access data ​in Hive, Impala, or HDFS with KNIME Analytics Platform.

Create and execute Apache Spark applications within KNIME Analytics Platform. Visual programming allows code-free big data analysis, while scripting of jobs allows detailed control when needed.

Conduct predictive analytics and scoring on Apache Spark ​using PMML models and integrate complex statistics and machine learning with Spark MLlib.

Mix and match local and Hadoop execution ​within the same workflow.

R and Python Scripting
R and Python Scripting

Add custom functionality ​with native R, Python (versions 2 and 3), and Java scripting capabilities - from custom Apache Spark jobs, to visualizations or advanced analytics, and machine learning.

Run scripts seamlessly in combination with other KNIME nodes within a single workflow. Document individual steps, allowing for large scale deployment.

H2O Machine Learning
H2O Machine Learning

Take advantage of H2O machine learning and choose from a variety of high performance algorithms (Gradient Boosted Trees, Generalized Linear Models, Random Forest etc).

Train and validate ​models in H2O using data partitioners, cross validation, binomial, and multinomial scoring.

Integrate with existing KNIME nodes for data prep and cleansing, visualization, or hyperparameter optimization, combining them directly with H2O functionality.

Deep Learning
Deep Learning

Load, create, edit, train, and execute deep neural networks within KNIME Analytics Platform.

Access a variety of cutting edge deep learning frameworks,​ such as TensorFlow, CNTK, and others via Keras or DeepLearning4J.

Fine tune trained networks to your analysis problem. A rich variety of unstructured (text, images, etc) and structured data types can directly be used for training and prediction.

Google Sheets
Google Sheets

Read data from a Google Sheet​, write information to new sheets, or modify existing sheets.

Carry out various tasks ​such as reading or adding headers, substituting missing values, and automatically opening Google Sheets.

Log in directly from the node configuration​ or provide credential files (if preferred).

And More...
And more...

Create custom JavaScript visualizations​, utilizing state of the art visualization libraries, for example D3.

Connect to Azure or AWS​ and work with your cloud data, stored in S3 or Azure Blobstore.

Search for Tweets on Twitter​, retrieve information about users, Tweet directly via KNIME, and more.

Visualize geo-spatial information ​with open street maps.

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