You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
Data-Science-For-Beginners/5-Data-Science-In-Cloud
Jasmine Greenaway 8bfd8d007d
Merge pull request #224 from sarthakregmi/assignment
3 years ago
..
17-Introduction Merge pull request #224 from sarthakregmi/assignment 3 years ago
18-Low-Code edit boolean examples 3 years ago
19-Azure created assignment.hi.md 3 years ago
images moving images around, standardizing paths, removing unused solutions files 3 years ago
translations Rename README.Nepali.md to README.ne.md 3 years ago
README.md Update README.md 3 years ago

README.md

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)