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Fundamentals of Data Engineering

Xebia

The following is a review of the book Fundamentals of Data Engineering by Joe Reis and Matt Housley, published by O’Reilly in June of 2022, and some takeaway lessons. This book is as good for a project manager or any other non-technical role as it is for a computer science student or a data engineer.

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Turing nabs $32M more for an AI-based platform to source and manage engineers remotely

TechCrunch

” It currently has a database of some 180,000 engineers covering around 100 or so engineering skills, including React, Node, Python, Agular, Swift, Android, Java, Rails, Golang, PHP, Vue, DevOps, machine learning, data engineering and more. Remote work = immediate opportunity.

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How GoDaddy built a category generation system at scale with batch inference for Amazon Bedrock

AWS Machine Learning - AI

This post was co-written with Vishal Singh, Data Engineering Leader at Data & Analytics team of GoDaddy Generative AI solutions have the potential to transform businesses by boosting productivity and improving customer experiences, and using large language models (LLMs) in these solutions has become increasingly popular.

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Predictive analytics helps Fresenius anticipate dialysis complications

CIO

Our primary challenge was in our ability to scale the real-time data engineering, inferences, and real-time monitoring to meet service-level agreements during peak loads (6K messages per second, 19MBps with 60K concurrent lambda invocations per second) and throughout the day (processing more than 500 million messages daily, 24/7).”

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Building a Machine Learning Application With Cloudera Data Science Workbench And Operational Database, Part 1: The Set-Up & Basics

Cloudera

Python is used extensively among Data Engineers and Data Scientists to solve all sorts of problems from ETL/ELT pipelines to building machine learning models. Apache HBase is an effective data storage system for many workflows but accessing this data specifically through Python can be a struggle. Introduction.

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How Mixbook used generative AI to offer personalized photo book experiences

AWS Machine Learning - AI

The inference pipeline is powered by an AWS Lambda -based multi-step architecture, which maximizes cost-efficiency and elasticity by running independent image analysis steps in parallel. He leads a product-engineering team responsible for transforming Mixbook into a place for heartfelt storytelling. DJ Charles is the CTO at Mixbook.

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The hacker's guide to uncertainty estimates

Erik Bernhardsson

apply ( lambda t : t. boxplot ( data = d , x = 'Month' , y = 'Weight (kg)' ). I’m looking for data engineers to join my team at Better ! I recommend the excellent Seaborn package if we just want to get some basic idea of distributions and uncertainty estimates. DataFrame ({ 'x' : xs , 't' : ts , 'Weight (kg)' : ys }).

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