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CI/CD for Data Pipelines: A Game-Changer with AnalyticsCreator

Data Science Blog

Continuous Integration and Continuous Delivery (CI/CD) for Data Pipelines: It is a Game-Changer with AnalyticsCreator! The need for efficient and reliable data pipelines is paramount in data science and data engineering. Data Lakes : It supports MS Azure Blob Storage.

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Feature Platforms?—?A New Paradigm in Machine Learning Operations (MLOps)

IBM Data Science in Practice

Hidden Technical Debt in Machine Learning Systems More money, more problems — Rise of too many ML tools 2012 vs 2023 — Source: Matt Turck People often believe that money is the solution to a problem. In regards to the challenge of operationalizing machine learning, this problem prompted a surge of investment to find a solution.

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10 reasons to learn Data Science

Pickl AI

Summary: Are you still wondering whether or not you should pursue your career as a Data Scientist? This blog breaks the ice and unfolds 10 reasons to learn Data Science. 10 reasons to learn Data Science The rapid increase in digitization has created volumes of data. million new job opportunities.

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How The Explosive Growth Of Data Access Affects Your Engineer’s Team Efficiency

Smart Data Collective

In fact, you may have even heard about IDC’s new Global DataSphere Forecast, 2021-2025 , which projects that global data production and replication will expand at a compound annual growth rate of 23% during the projection period, reaching 181 zettabytes in 2025. zettabytes of data in 2020, a tenfold increase from 6.5

Big Data 119
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Use LangChain with PySpark to process documents at massive scale with Amazon SageMaker Studio and Amazon EMR Serverless

AWS Machine Learning Blog

By using the Livy REST APIs , SageMaker Studio users can also extend their interactive analytics workflows beyond just notebook-based scenarios, enabling a more comprehensive and streamlined data science experience within the Amazon SageMaker ecosystem. elasticmapreduce", "arn:aws:s3:::*.elasticmapreduce/*"

AWS 123
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Four approaches to manage Python packages in Amazon SageMaker Studio notebooks

Flipboard

Check that the SageMaker image selected is a Conda-supported first-party kernel image such as “Data Science.” From the new notebook, choose the “Python 3 (Data Science)” kernel. He develops and codes cloud native solutions with a focus on big data, analytics, and data engineering.

Python 123
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Use Amazon SageMaker Model Card sharing to improve model governance

AWS Machine Learning Blog

In addition to data engineers and data scientists, there have been inclusions of operational processes to automate & streamline the ML lifecycle. Depending on your governance requirements, Data Science & Dev accounts can be merged into a single AWS account.

AWS 131