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nibble.ai weekly #15: Data Scientist vs Data Engineer. New Udacity Tensorflow 2.0 course...

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Hi everyone. Experimenting with a new design, tell us what you think! [email protected]
 

nibble.ai dispatch

May 15 · Issue #15 · View online
Curated essays about the future of Data Science. Production Data Science and learning resources for continuous learning. Covers Data Science, Data Engineering, MLOps & DataOps. Curated by people at https://nibble.ai/

Hi everyone. Experimenting with a new design, tell us what you think! [email protected]

I recently talked to a few people wondering about the differences between data science and data engineering, these articles should enlighten you:
The risks of artificial intelligence
An in-depth article by McKinsey about the risks of artificial intelligence.
With great power comes great responsibility. Organisations can mitigate the risks of applying artificial intelligence and advanced analytics by embracing three principles.
Choose the right AI Business Model
A strong Business Model is a critical element to any project, AI/data projects are no exceptions, and as usual with everything data, it requires some adjustment, read more here.
Learning resources
Intro to TensorFlow 2.0 for Deep Learning
Pandas Under The Hood
Testing in Airflow
Parallel Processing in Python
Non-inferiority trials
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