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A simple approach to wine classification problem using chemical analysis, wrapped and presented as a Dara app.

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My first Dara App: Wine Classification Problem


A. Screenshots

Home page home page

EDA page home page

Classification page home page

B. Installation and Setup

1. Poetry

  • Install curl -sSL https://install.python-poetry.org | python3 -

  • Add export PATH="$HOME/.local/bin:$PATH" to .zshrc (source)

  • Use poetry --version

2. Create new app and install dara

  • Create new app

    • In PyCharm with new poetry env
    • manually using mkdir and poetry init
  • Run poetry install

  • Install poetry add dara-core --extras all

C. Creating a basic app tutorial

1. Hello World

2. Add new pages

  • Install dependencies to build a page that cna handle data: poetry add scikit-learn

  • Create a pages subdir and add new pages in python there

  • Add new pages to the main config using config.add()

3.Future Components

  • Choose model from list of model e.g., RF, GBMs, SVM, ...
  • More model validation metrics (ROC curve, precision/recall trade-off)
  • More EDA (similar to pandas-profiling)

Contact

  • Email address: adam[dot]jaamour[at]causalens[dot]com

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A simple approach to wine classification problem using chemical analysis, wrapped and presented as a Dara app.

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