Data engineering and machine learning pipelines are both very different but oddly can feel very similar. Many ML engineers I have talked to in the past rely on tools like Airflow to deploy their batch models.
So I wanted to discuss the difference between data engineering vs machine learning pipelines.
To answer this question, I pulled in Sarah Floris, who is both an experienced data engineer as well as the author behind the newsletter The Dutch Engineer.
So let’s dive in.
You can read the full article here - seattledataguy.substack.com/p...
You can follow Sarah Floris here - / sarah-floris
Also if you're looking for a new tool to build your data engineering or machine learning pipelines, check out - bit.ly/41h6Pjy
If you enjoyed this video, check out some of my other top videos.
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Tags: Data engineering projects, Data engineer project ideas, data project sources, data analytics project sources, data project portfolio
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About me:
I have spent my career focused on all forms of data. I have focused on developing algorithms to detect fraud, reduce patient readmission and redesign insurance provider policy to help reduce the overall cost of healthcare. I have also helped develop analytics for marketing and IT operations in order to optimize limited resources such as employees and budget. I privately consult on data science and engineering problems both solo as well as with a company called Acheron Analytics. I have experience both working hands-on with technical problems as well as helping leadership teams develop strategies to maximize their data.
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29 июл 2024
