data-science-pipelines

There are 5 repositories under data-science-pipelines topic.

  • Invictify/Jupter-Notebook-REST-API

    Run your jupyter notebooks as a REST API endpoint. This isn't a jupyter server but rather just a way to run your notebooks as a REST API Endpoint.

    Language:Jupyter Notebook753010

  • SciEcon/SRS2021

    A Data Science pipeline for Algorithmic Trading: A comparative study in applications to Finance and cryptoeconomics

    12106

  • githubfoam/kind-travisci

    kind k8s pipeline

    Language:Shell121

  • IBMDeveloperMEA/Data-Science-Lifecycle-Collect-Clean-Predict-Analyze-your-Data

    Customer churn is an important aspect for any business, it gives them insights about their prospective customers. In this tutorial we will be predicting customer churn of car owners. We will be utilizing Watson data refinery to alter our data, and then use AutoAI to rapdliy develop a classfication machine learning model in a matter of minutes and predict our customer chrun.

    301

  • RegaipKURT/ScikitLearnWithFUN

    This repository shows the implementation of machine learning algorithms, data pipelines and data visualization with scikit-learn and python.

    Language:Jupyter Notebook201