Exercise: Sagemaker Scavenger Hunt

  • Topic: Build a Sagemaker based Data Science project
  • Estimated time: 45 minutes
  • People: Individual or Final Project Team
  • Slack Channel: #noisy-exercise-chatter

  • Directions:

  • Part A: Get the airline data into your own Sagemaker.
  • Part B: Performance the Data Science worflow:
    • Ingest: Process the data
    • EDA: Visualize and Explore data
    • Model: Create some form of a model
    • Conclusion
  • Part C: Consider trying multiple visualization libraries: Plotly, Vega, Bokeh and Seaborn
  • Part D: Download notebook and upload into Colab, then check notebook in a Github porfolio repo. *Hints: You may want to truncate the data and upload a small version into Github using unix shuf command.
shuf -n 100000 en.openfoodfacts.org.products.tsv\
> 10k.sample.en.openfoodfacts.org.products.tsv
1.89s user 0.80s system 97% cpu 2.748 total