DL Python Network Creator

Source

This node allows custom creation of a (Python compatible) deep learning network in a local Python installation via a user-defined script. The path to the Python executable has to be configured in Preferences → KNIME → Python. It also allows to import Jupyter notebooks as Python modules via the knime_jupyter module that is part of the Python workspace.

Output Ports

  1. Type: DLPythonNetworkPortObject
    The output deep learning network. This is the content of the variable output_network which has to be defined in the script and has to be a deep learning network known to KNIME. The network can then be used in common "DL Python" nodes or in nodes which are specific to the network type.

  1. Image Recognition for Retail Use Case: Data Preparation & Building Convolutional Neural Network (CNN) Workflow

    We used neural networks for the image recognition task. Neural networks are massively parallel adaptive processing struc…
    Users > knime > Examples > 50_Applications > 47_Image_Recognition_for_Retail

  2. Semantic Segmentation with Deep Learning in KNIME

    deep learning image processing image analysis computer vision unet neural network segmentation semantic segmentation encoder decoder pixel classification
    This workflow shows how the new KNIME Keras integration can be used to train and deploy a specialized deep neural networ…
    Users > shima0011 > 04_Analytics > 14_Deep_Learning > 02_Keras

  3. Sentiment Analysis

    deep learning keras text classification classification lstm embedding text analysis sequence analysis sentiment analysis sequence classification neural network text processing
    This workflow shows how to train a simple neural network for text classification, in this case sentiment analysis. The u…
    Users > shima0011 > 04_Analytics > 14_Deep_Learning > 02_Keras

  4. Read Images and Train ResNet

    Life Science Image Analysis Deep Learning Keras
    This workflow reads image patches downloaded and prepared by the previous workflows in the workflow group. It loads the …
    Users > davek

  5. Read Images and Train VGG

    Life Science Image Analysis Deep Learning Keras
    This workflow reads image patches downloaded and prepared by the previous workflows in the workflow group. It loads the …
    Users > davek

  6. Train MNIST classifier

    deep learning TensorFlow image classification
    This workflow trains a simple convolutional neural network (CNN) on the MNIST dataset via TensorFlow.
    Users > shima0011 > 04_Analytics > 14_Deep_Learning > 03_TensorFlow

  7. Train simple CNN

    deep learning Keras image classification
    In this workflow we create a simple Convolutional Neural Network using the DL Python Network Creator. We train this netw…
    Users > shima0011 > 04_Analytics > 14_Deep_Learning > 02_Keras > 04_Cats_and_Dogs

  8. Read Images and Train VGG

    Life Science Image Analysis Deep Learning Keras
    This workflow reads image patches downloaded and prepared by the previous workflows in the workflow group. It loads the …
    Users > knime > Examples > 50_Applications > 31_Histopathology_Blog_Post

  9. Semantic Segmentation with Deep Learning in KNIME

    deep learning image processing image analysis computer vision unet neural network segmentation semantic segmentation encoder decoder pixel classification NLP Natural Language Processing Python
    This workflow shows how the new KNIME Keras integration can be used to train and deploy a specialized deep neural networ…
    Users > knime > Examples > 04_Analytics > 14_Deep_Learning > 02_Keras

  10. KNIME Deep Learning - Train MNIST classifier

    deep learning Keras image classification
    This workflow trains a simple convolutional neural network (CNN) on the MNIST dataset via Keras.
    Users > shima0011 > 04_Analytics > 14_Deep_Learning > 02_Keras

Extension

This node is part of the extension

KNIME Deep Learning - Keras Integration

 v4.0.0

Short Link

Drag node into KNIME Analytics Platform