Hub
Pricing About
  • Software
  • Blog
  • Forum
  • Events
  • Documentation
  • About KNIME
  • KNIME Community Hub
  • knime
  • Spaces
  • Examples
  • 04_Analytics
  • 14_Deep_Learning
  • 04_TensorFlow2
  • 04_Train_a_MLP
WorkflowWorkflow

Train a simple Multilayer Perceptron using TensorFlow 2

TensorFlow 2 Deep Learning Tf TensorFlow MLP
+1
KNIME profile image

Last edited: 

Drag & drop
Like
Download workflow
Copy short link
Workflow preview
This workflow shows how to train a simple multilayer perceptron for classification. It is demonstrated how the "DL Python Network Creator" can be used to create a simple neural network using the tf.keras API and how the "DL Python Network Learner" can be used to train the created network on data. In order to run the example, please make sure you have the following KNIME extensions installed: * KNIME Deep Learning - TensorFlow 2 Integration (Labs) You also need a local Python installation that includes TensorFlow 2. Please refer to https://docs.knime.com/latest/deep_learning_installation_guide/#dl_python_setup for installation recommendations and further information.

External resources

  • KNIME Deep Learning Integration Installation Guide

Used extensions & nodes

Created with KNIME Analytics Platform version 4.2.3
  • Go to item
    KNIME Base nodes Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.2.0

    KNIME profile image
    knime
  • Go to item
    KNIME Deep Learning - Keras Integration Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.2.0

    KNIME profile image
    knime
  • Go to item
    KNIME Deep Learning - TensorFlow 2 Integration Trusted extension

    KNIME AG, Zurich, Switzerland

    Versions 4.2.0, 4.2.3

    KNIME profile image
    knime
  1. Go to item
  2. Go to item
  3. Go to item
  4. Go to item
  5. Go to item
  6. Go to item
Loading deployments
Loading ad hoc executions

Legal

By using or downloading the workflow, you agree to our terms and conditions.

Discussion
Discussions are currently not available, please try again later.

KNIME
Open for Innovation

KNIME AG
Talacker 50
8001 Zurich, Switzerland
  • Software
  • Getting started
  • Documentation
  • E-Learning course
  • Solutions
  • KNIME Hub
  • KNIME Forum
  • Blog
  • Events
  • Partner
  • Developers
  • KNIME Home
  • KNIME Open Source Story
  • Careers
  • Contact us
Download KNIME Analytics Platform Read more on KNIME Business Hub
© 2023 KNIME AG. All rights reserved.
  • Trademarks
  • Imprint
  • Privacy
  • Terms & Conditions
  • Credits