{"repo":"Minyus/kedro-starters-sklearn","free":true,"listed":false,"github":"https://github.com/Minyus/kedro-starters-sklearn","clone":"git clone https://github.com/Minyus/kedro-starters-sklearn.git","description":"Kedro starter templates using Scikit-learn and optionally MLflow","language":"Python","stars":10,"topics":[],"license":null,"category":"saas-starters-boilerplates","readme_excerpt":"kedro-starters-sklearn This repository provides the following preserved starter templates updated for kedro==1.3.1 . - sklearn-iris trains a Logistic Regression model using Scikit-learn. - sklearn-mlflow-iris adds experiment tracking feature using MLflow. Pipeline visualized by Kedro-viz sklearn-iris template Iris dataset Iris dataset is included and used by default. - Modification: for each species, setosa is encoded to 0, versicolor is encoded to 1, and virginica samples were removed. - Split: for each species, the first 25 samples are included in train.csv , and the last 25 samples are included in test.csv . How to use 1. Install dependencies. 2. Generate your Kedro starter project from sklearn-iris directory. As explained in the Kedro documentation, enter project name , repo name , and python package . Note: as your Python package name, choose a unique name and avoid a generic name such as test or sklearn used by another package. You can see the list of importable packages by running python -c \"help('modules')\" . 3. Change the current directory to the generated project directory. 4. Install project dependencies and run the project. Option to use Kaggle Titanic dataset 1. Download Kaggle Titanic dataset 2. Replace train.csv and test.csv in /path/to/project/directory/data/01 raw directory 3. Modify /path/to/project/directory/conf/base/parameters.yml to set parameters appropriate for the dataset (commented out by default) sklearn-mlflow-iris template This template integrates","default_branch":null,"files":null,"tree":[],"storefront":"/r/Minyus","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/Minyus/kedro-starters-sklearn/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}