đŸ”¥Entire Machine learning lifecycle (High Level View & Detailed View) with AWS


Amazon SageMaker is a cloud machine learning platform that helps data scientists and developers to accelerate innovation with purpose-built tools for every step of ML development, including labeling, data preparation, feature engineering, statistical bias detection, auto-ML, training, tuning, hosting, explainability, monitoring, and workflows.


These newer lifecycle tasks and their corresponding Amazon SageMaker capabilities include the following: 1. SageMaker Data Wrangler for feature


transformation


2. SageMaker Processing for preprocessing data 3. SageMaker Feature Store (offline) for


standardization of features


4. SageMaker Clarify for bias detection pre- and post-training and for post-inference interpretability of results


5. SageMaker ML Lineage Tracking to help with


governance of ML artifacts


6. SageMaker Model Registry for model and metadata


storage


7. SageMaker Pipelines for end to end workflow automation