Remove AWS Remove Data Preparation Remove Data Wrangling
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Migrate Amazon SageMaker Data Wrangler flows to Amazon SageMaker Canvas for faster data preparation

AWS Machine Learning Blog

Amazon SageMaker Data Wrangler provides a visual interface to streamline and accelerate data preparation for machine learning (ML), which is often the most time-consuming and tedious task in ML projects. About the Authors Charles Laughlin is a Principal AI Specialist at Amazon Web Services (AWS).

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Unlock the power of data governance and no-code machine learning with Amazon SageMaker Canvas and Amazon DataZone

AWS Machine Learning Blog

Amazon DataZone is a data management service that makes it quick and convenient to catalog, discover, share, and govern data stored in AWS, on-premises, and third-party sources. An Amazon DataZone domain and an associated Amazon DataZone project configured in your AWS account. Choose Data Wrangler in the navigation pane.

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Data Transformation and Feature Engineering: Exploring 6 Key MLOps Questions using AWS SageMaker

Towards AI

This article is part of the AWS SageMaker series for exploration of ’31 Questions that Shape Fortune 500 ML Strategy’. Automation] How can the transformation steps be applied in real-time to the live data before inference? To prepare the data for models, a data scientist often needs to transform, clean, and enrich the dataset.

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Data Science Career Paths: Analyst, Scientist, Engineer – What’s Right for You?

How to Learn Machine Learning

Data Storage and Management Once data have been collected from the sources, they must be secured and made accessible. The responsibilities of this phase can be handled with traditional databases (MySQL, PostgreSQL), cloud storage (AWS S3, Google Cloud Storage), and big data frameworks (Hadoop, Apache Spark).

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15 Fan-Favorite Speakers & Instructors Returning for ODSC East 2025

ODSC - Open Data Science

With over 30 years in techincluding key roles at Hugging Face, AWS, and as a startup CTOhe brings unparalleled expertise in cloud computing and machine learning. As the author of *Hands-On Data Analysis with Pandas* (now in its second edition), she is a recognized expert in making data actionable.

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Roadmap to Learn Data Science for Beginners and Freshers in 2023

Becoming Human

There is a position called Data Analyst whose work is to analyze the historical data, and from that, they will derive some KPI s (Key Performance Indicators) for making any further calls. For Data Analysis you can focus on such topics as Feature Engineering , Data Wrangling , and EDA which is also known as Exploratory Data Analysis.

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Must-Have Prompt Engineering Skills for 2024

ODSC - Open Data Science

Databricks: Powered by Apache Spark, Databricks is a unified data processing and analytics platform, facilitates data preparation, can be used for integration with LLMs, and performance optimization for complex prompt engineering tasks. Kubernetes: A long-established tool for containerized apps.