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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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        • 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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        • Wrapping an exported model in a CLI tool
    • Plugins development
      • Foreword
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      • Datasets
        • 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
      • Recipes
        • Creating a plugin Recipe component
        • Writing a custom recipe to remove outliers from a dataset
      • Webapps
        • Turning an existing webapp into a webapp plugin component
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      • Common subjects on webapps
        • Accessible resources from webapps
        • Creating an API endpoint from webapps
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        • Bokeh: Your first webapp
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        • Create an empty dash webapp
        • Dash: your first webapp
        • Display a Bar chart using Dash
        • Create a simple admin project dashboard using Dash.
        • Create a simple multi-page webapp
        • Uploading or downloading files with Managed Folders in Dash
        • How to create a form for data input?
        • Simple scoring application
        • Creating an API endpoint for using an LLM-Based agent
        • Using Dash and LLM Mesh to build a GPT-powered web app assistant
        • 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
        • Use Custom Static Files (Javascript, CSS) in a Webapp
        • Upload to Dataiku DSS in a Webapp
        • Download from a Dataiku DSS Webapp
        • 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
        • Basic setup: Quickstart with Angular & Vue Templates
        • 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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      • Importing tables as datasets
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      • SQL Query
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      • Index of the dataiku package
      • Index of the dataikuapi package
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        • API for plugin formats
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You are viewing the developer guide for version 13 of DSS.
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  • Tutorials
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  • File Format
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File Format#

This section contains several learning materials about the plugin component: File Format.

  • Writing a plugin File Format component to allow ICal import in Dataiku
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Writing a plugin File Format component to allow ICal import in Dataiku
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Creating a plugin Dataset component
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