Skip to content

Fix documentation issues in README files #4865

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
wants to merge 1 commit into
base: default
Choose a base branch
from
Open

Fix documentation issues in README files #4865

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion end_to_end_ml_lifecycle/README.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -6,4 +6,4 @@ These examples are a diverse collection of end-to-end notebooks that demonstrate

- [Customer Churn Prediction with Amazon SageMaker Autopilot](sm-autopilot_customer_churn.ipynb)
- [Housing Price Prediction with Amazon SageMaker Autopilot](sm-autopilot_linear_regression_california_housing.ipynb)
- [Time-Series Forecasting with Amazon SageMaker Autopilot](sm-sm-autopilot_time_series_forecasting.ipynb)
- [Time-Series Forecasting with Amazon SageMaker Autopilot](sm-autopilot_time_series_forecasting.ipynb)
2 changes: 1 addition & 1 deletion prepare_data/README.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -2,7 +2,7 @@

### Prepare Data

The example notebooks within this folder showcase Sagemaker's data preparation capabilities. Data preparation in machine learning refers to the process of collecting, preprocessing, and organizing raw data to make it suitable for analysis and modeling.
The example notebooks within this folder showcase SageMaker's data preparation capabilities. Data preparation in machine learning refers to the process of collecting, preprocessing, and organizing raw data to make it suitable for analysis and modeling.

- [Data Wrangler Data Prep Widget - Example Notebook](sm-data_wrangler_data_prep_widget/sm-data_wrangler_data_prep_widget.ipynb)
- [Amazon SageMaker Feature Store: Feature Processor Introduction](sm-feature_store_feature_processor/sm-feature_store_feature_processor.ipynb)
Expand Down