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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? We were able to identify feature correlations, data imbalance, and datatype requirements.

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40 Must-Know Data Science Skills and Frameworks for 2023

ODSC - Open Data Science

Cloud Services The only two to make multiple lists were Amazon Web Services (AWS) and Microsoft Azure. Most major companies are using one of the two, so excelling in one or the other will help any aspiring data scientist. Saturn Cloud is picking up a lot of momentum lately too thanks to its scalability.

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Training Sessions Coming to ODSC APAC 2023

ODSC - Open Data Science

Build Classification and Regression Models with Spark on AWS Suman Debnath | Principal Developer Advocate, Data Engineering | Amazon Web Services This immersive session will cover optimizing PySpark and best practices for Spark MLlib. Free and paid passes are available now–register here.

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Roadmap to Learn Data Science for Beginners and Freshers in 2023

Becoming Human

You have to learn only those parts of technology that are useful in data science as well as help you land a job. Don’t worry; you have landed at the right place; in this article, I will give you a crystal clear roadmap to learning data science. Because this is the only effective way to learn Data Analysis.

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Top Data Analytics Skills and Platforms for 2023

ODSC - Open Data Science

Skills like effective verbal and written communication will help back up the numbers, while data visualization (specific frameworks in the next section) can help you tell a complete story. Data Wrangling: Data Quality, ETL, Databases, Big Data The modern data analyst is expected to be able to source and retrieve their own data for analysis.

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How to Shift from Data Science to Data Engineering

ODSC - Open Data Science

Data scientists typically have strong skills in areas such as Python, R, statistics, machine learning, and data analysis. Believe it or not, these skills are valuable in data engineering for data wrangling, model deployment, and understanding data pipelines. First, articles.

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Data Analysis at Warp Speed: Explore the World of Polars

Mlearning.ai

Goal The objective of this post is to demonstrate how Polars performance is much better than other open-source libraries in a variety of data analysis tasks, such as data cleaning, data wrangling, and data visualization. ? Contributions welcome ! ?Acknowledgments