This is an automated email from the ASF dual-hosted git repository. xqhu pushed a commit to branch master in repository https://gitbox.apache.org/repos/asf/beam.git
The following commit(s) were added to refs/heads/master by this push: new 0ba89bbbb8f YAML example suite minor updates (#36074) 0ba89bbbb8f is described below commit 0ba89bbbb8f627c49c21fd763278c0f16791c12f Author: Charles Nguyen <phucnh...@gmail.com> AuthorDate: Sat Sep 6 15:02:38 2025 -0400 YAML example suite minor updates (#36074) --- sdks/python/apache_beam/yaml/examples/README.md | 3 ++- .../ml/fraud_detection/fraud_detection_mlops_beam_yaml_sdk.ipynb | 2 +- 2 files changed, 3 insertions(+), 2 deletions(-) diff --git a/sdks/python/apache_beam/yaml/examples/README.md b/sdks/python/apache_beam/yaml/examples/README.md index b053e3e6236..25765e5d48b 100644 --- a/sdks/python/apache_beam/yaml/examples/README.md +++ b/sdks/python/apache_beam/yaml/examples/README.md @@ -265,7 +265,8 @@ Examples that include ML-specific transforms such as `RunInference` and `MLTransform`: - Streaming Sentiment Analysis ([documentation](https://github.com/apache/beam/tree/master/sdks/python/apache_beam/yaml/examples/transforms/ml/sentiment_analysis)) ([pipeline](https://github.com/apache/beam/blob/master/sdks/python/apache_beam/yaml/examples/transforms/ml/sentiment_analysis/streaming_sentiment_analysis.yaml)) - Streaming Taxi Fare Prediction ([documentation](https://github.com/apache/beam/tree/master/sdks/python/apache_beam/yaml/examples/transforms/ml/taxi_fare)) ([pipeline](https://github.com/apache/beam/blob/master/sdks/python/apache_beam/yaml/examples/transforms/ml/taxi_fare/streaming_taxifare_prediction.yaml)) -- Batch Log Analysis ML Workflow ([documentation](https://github.com/apache/beam/tree/master/sdks/python/apache_beam/yaml/examples/transforms/ml/log_analysis)) ([pipeline](https://github.com/apache/beam/blob/master/sdks/python/apache_beam/yaml/examples/transforms/ml/log_analysis/batch_log_analysis.yaml)) +- Batch Log Analysis ML Workflow ([documentation](https://github.com/apache/beam/tree/master/sdks/python/apache_beam/yaml/examples/transforms/ml/log_analysis)) ([pipeline](https://github.com/apache/beam/blob/master/sdks/python/apache_beam/yaml/examples/transforms/ml/log_analysis/batch_log_analysis.sh)) +- Fraud Detection MLOps Workflow ([documentation](https://github.com/apache/beam/blob/master/sdks/python/apache_beam/yaml/examples/transforms/ml/fraud_detection/README.md)) ([pipeline](https://github.com/apache/beam/blob/master/sdks/python/apache_beam/yaml/examples/transforms/ml/fraud_detection/fraud_detection_mlops_beam_yaml_sdk.ipynb)) More information can be found about aggregation transforms [here](https://beam.apache.org/documentation/sdks/yaml-combine/). diff --git a/sdks/python/apache_beam/yaml/examples/transforms/ml/fraud_detection/fraud_detection_mlops_beam_yaml_sdk.ipynb b/sdks/python/apache_beam/yaml/examples/transforms/ml/fraud_detection/fraud_detection_mlops_beam_yaml_sdk.ipynb index 52f81b56f6b..017de31d5ca 100644 --- a/sdks/python/apache_beam/yaml/examples/transforms/ml/fraud_detection/fraud_detection_mlops_beam_yaml_sdk.ipynb +++ b/sdks/python/apache_beam/yaml/examples/transforms/ml/fraud_detection/fraud_detection_mlops_beam_yaml_sdk.ipynb @@ -37,7 +37,7 @@ "\n", "<table><tbody><tr>\n", " <td style=\"text-align: center\">\n", - " <a href=\"https://console.cloud.google.com/vertex-ai/colab/import/https:%2F%2Fraw.githubusercontent.com%2Fapache%2Fbeam%2Fblob%2Fmaster%2Fsdks%2Fpython%2Fapache_beam%2Fyaml%2Fexamples%2Ftransforms%2Fml%2Ffraud_detection%2Ffraud_detection_mlops_beam_yaml_sdk.ipynb\">\n", + " <a href=\"https://console.cloud.google.com/vertex-ai/colab/import/https:%2F%2Fraw.githubusercontent.com%2Fapache%2Fbeam%2Frefs%2Fheads%2Fmaster%2Fsdks%2Fpython%2Fapache_beam%2Fyaml%2Fexamples%2Ftransforms%2Fml%2Ffraud_detection%2Ffraud_detection_mlops_beam_yaml_sdk.ipynb\">\n", " <img alt=\"Google Cloud Colab Enterprise logo\" src=\"https://lh3.googleusercontent.com/JmcxdQi-qOpctIvWKgPtrzZdJJK-J3sWE1RsfjZNwshCFgE_9fULcNpuXYTilIR2hjwN\" width=\"32px\"><br> Run in Colab Enterprise\n", " </a>\n", " </td>\n",