5 votes
Accepted

MLOps for beginner

a. For a beginner I would suggest the fullstackdeeplearning course, it's a modern overview of tools and best practices for ML in production. As you can see below, there are a lot of moving pieces. b. ...
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  • 196
5 votes

MLOps for beginner

You can do live learning but most models don't require it, because many businesses don't need to learn directly from new input. Nevertheless, you can apply an automated task every time range (day, ...
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3 votes

How to use LAT/LNG as predictor variables

If you want to predict at locations where you don't have data, and you assume that there is a continuous surface of your variable of interest (ie it is defined at all locations) then you can use ...
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  • 1,932
2 votes

Using Latitude/Longitude and site ID in classification of daily air pollution levels

Are classifiers built on the first dataset valid as they are basing some of their predictive value simply on the site ID? Is site ID (and to a similar extend Lat/Lon) a valid feature to include? It's ...
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  • 2,319
1 vote

Why can Random Forest "handle missing values and cardinality well compared to linear regression"?

Generally, random forests are a much more sophisticated method than linear regression: it's an ensemble method with multiple decision trees, and a single decision tree is already a much more flexible ...
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  • 21.8k
1 vote

Which Model for predicting flight delays is appropriate except Random Forest and Decision Tree? (Monte Carlo?)

Weather is responsible for 90% of the flight delays. How is it possible to make reliable predictions with just 10% of the remaining causes? (if their data is available) You have an existing map called ...
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