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  • Getting started
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    • MLOps lifecycle
    • The Dataiku Python packages
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      • Step 1: Prepare the input dataset for ML modeling
      • Step 2: Test different Machine Learning models for heart failures prediction
      • Step 3: Create a Dataiku Saved Model using the best-performing model
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        • Programmatic RAG with Dataiku’s LLM Mesh and Langchain
        • Using LLM Mesh to benchmark zero-shot classification models
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        • Load and re-use a TensorFlow Hub model
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        • Importing serialized scikit-learn pipelines as Saved Models for MLOps
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        • Creating a plugin Dataset component
      • File Format
        • Writing a plugin File Format component to allow ICal import in Dataiku
      • Macros
        • Creating a plugin Macro component
        • Writing a macro for project creation
        • Writing a macro for managing regression tests
      • Processor plugin component
        • Creating a plugin Processor component
      • Prediction algorithm
        • Creating a plugin Prediction Algorithm component
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        • Creating a plugin Recipe component
        • Writing a custom recipe to remove outliers from a dataset
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        • Turning an existing webapp into a webapp plugin component
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      • Common subjects on webapps
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        • Bokeh: Your first webapp
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        • Create an empty dash webapp
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        • Display a Bar chart using Dash
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        • How to create a form for data input?
        • Simple scoring application
        • Creating an API endpoint for using an LLM-Based agent
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        • Creating a Dash application using an LLM-based agent
      • Gradio
        • Gradio: your first web application
        • Creating a Gradio application using an LLM-based agent
      • Standard (HTML, CSS, JS)
        • HTML/CSS/JS: your first webapp
        • Adapt a D3.js Template in a Webapp
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        • How to create a form for data input?
        • Simple scoring application
      • Streamlit
        • Streamlit: your first webapp
      • Use your own framework.
        • Basic setup: Code studio template
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        • Basic setup: Deploy your web application
        • Advanced setup: Code Studio template creation
        • Advanced setup: Web application creation and publication
      • Voilà
        • Voilà: your first web application
        • Creating a Voilà application using an LLM-based agent
  • API Reference
    • Python
      • Index
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      • The main API client
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      • SQL Query
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You are viewing the developer guide for version 13 of DSS.
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  • Tutorials
  • Plugins Development
  • Processor Plugin Component
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Processor plugin component#

This section contains learning materials about the plugin component: Preparation Processor.

  • Creating a plugin Processor component
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Creating a plugin Processor component
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Writing a macro for managing regression tests
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