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Differential Privacy - To protect individual data values by adding statistical "noise" to the analysis process. "Noise" is added to the data during analysis so that aggregations are staticstically consistent with the data distribution but non-deterministic. Epsilon - The amount of variation caused by adding noise is configurable through a parameter. A low epsilon value provides the most privacy,..

Pipeline - In Azure Machine Learning, a workflow of machine learning tasks in which each task is implemented as a step. PythoneScriptStep: Runs a specified Python script DataTransferStep: Uses Azure Data Factory to copy data between data stores DatabricksStep: Runs a notebook, script, or compiled JAR on a databricks cluster AdlaStep: Runs a U-SQL job in Azure Data Lake Analytics ParallelRunStep:..

Azure Machine Learning SDK Scalable, on-demand compute for machine learning workloads Data storage and connectivity to ingest data from a wide range sources ML workflow orchestration to automate model training, deployment, and management processes Model registration and management to track multiple versions of models and the data on which they were trained Metrics and monitoring for training exp..

3월에 Microsoft 사의 DP-100 Azure Data Scientist Associate 시험을 예약해두었습니다. AZ-900을 공부했던 방식과 같이 Microsoft Learn + Dump Exam 중심으로 Summary 올리며, 시험준비를 하려고 합니다. AZ-900 Fundamental Azure에 대해서는 요약본과 포스팅 & 시험 후기들이 많이 있는데, DP-100에 대해서는 많이 없더라구요. 그래서 저도 공부하고 여러분께 도움되고자 글 올려보도록 하겠습니다. Microsoft Learn에서는 크게 3가지로 Learning Path가 구분되어 있고, 그 밑으로 소주제들이 포함되어 있습니다. 일단 먼저 각 Learning Path를 한 번씩 공부해둔 상태입니다. 기본적인 Python을 다루..