Skip to content

Latest commit

 

History

History
21 lines (13 loc) · 1.5 KB

README.md

File metadata and controls

21 lines (13 loc) · 1.5 KB
Raw

Data Science in the Cloud

cloud-picture

Photo by Jelleke Vanooteghem from Unsplash

When it comes to doing data science with big data, the cloud can be a game changer. In the next three lessons, we are going to see what the cloud is and why it can be very helpful. We are also going to explore a heart failure dataset and build a model to help assess the probability of someone having a heart failure. We will use the power of the cloud to train, deploy and consume a model in two different ways. One way using only the user interface in a Low code/No code fashion, the other way using the Azure Machine Learning Software Developer Kit (Azure ML SDK).

project-schema

Topics

  1. Why use Cloud for Data Science?
  2. Data Science in the Cloud: The "Low code/No code" way
  3. Data Science in the Cloud: The "Azure ML SDK" way

Credits

These lessons were written with ☁️ and 💕 by Maud Levy and Tiffany Souterre

Data for the Heart Failure Prediction project is sourced from Larxel on Kaggle. It is licensed under the Attribution 4.0 International (CC BY 4.0)