microsoft / microsoft/WhatTheHack
[Proposal]: What The Hack for Data Science in Microsoft Fabric
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Description
Topic
Hi,
We are planning to create the what the hack for "data science in Microsoft Fabric". This hack will help customers to get an idea how any data scientist can use Microsoft fabric to build end to end data science process.
Below is the fictious use case:-
Contoso hospital has historical, anonymized heart condition data already present in their ADLS Gen 2 as part of their record-keeping solution. They want to leverage this data to create a new app that can help clinicians assess the heart failure risk of their patients, depending on a variety of factors. As an analyst at Contoso, you have been asked to use Microsoft Fabric to train a prediction model and deploy it on Realtime endpoints so that they can build an app on it which will be used by the doctors to predict the patient heart health.
Abstract/Learning Objectives
- Bringing data from external source to one lake.
- Preprocessing the data using data wrangler as well as copilot
- Training the model and registering the model.
- Generating batch/real time prediction
- Generating report on top of that.
Delivery Date
May 31st,2024.
Authors
juanlldc
Other
No response
Code of Conduct
- I agree to follow this project's Code of Conduct
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start from the proposal's learning objectives and the Contoso hospital heart-risk scenario. Define the hack's end-to-end material for ingestion, preprocessing, model training and registration, batch or real-time prediction, and reporting; it is done when these objectives are covered for the stated Microsoft Fabric use case.
Written by the indexing model from the issue text.
Assessment
- Domain
- content, data-engineering, documentation, machine-learning
- Issue type
- Documentation
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100