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Dataiku DSS
You are viewing the documentation for version 11 of DSS.
  • »
  • Machine learning »
  • Deep Learning

Deep LearningΒΆ

  • Introduction
  • Your first deep learning model
    • Create a code environment with the required packages
    • Create a Deep Learning analysis to solve a Prediction problem
    • Review the architecture of you Deep Learning model
    • Monitor the performance of your model during the training
  • Model architecture
    • Build Keras model
      • input_shapes
      • n_classes
      • Layer dimensions
    • Compile the model
  • Training
  • Multiple inputs
    • Regular multi-feature inputs
    • Custom-processed single-feature inputs
  • Using image features
    • Scoring images
  • Using text features
  • Runtime and GPU support
    • Code environment
    • Selection of GPU
    • Using multiple GPUs for training
  • Advanced topics
    • Start with weights from a previously trained model
    • How is the model trained?
    • Advanced training mode
      • Build sequence
      • Fit model
        • Usage of metrics in Callbacks
  • Troubleshooting
    • Using pre-trained models from Keras
    • Code environment lineage
    • TensorFlow session
    • ML API
    • Number of outputs in the model
    • Enforced code environment for Project
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