Don’t Democratize Data Science
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Don’t Democratize Data Science
1–6 of 6 posts
Re: Don’t Democratize Data Science
#2it’s a counterintuitive argument but I completely agree
Re: Don’t Democratize Data Science
#3it’s a counterintuitive argument but I completely agree
Can you imagine trying to democratize phd level mathematics? This boot camp shit has gotten insane.
Re: Don’t Democratize Data Science
#4So I do not think that this is a black/white situation.
I do agree, that any auto ml tool, cannot know what is the correct data sources for a specific use case, nor does it know the business case value of a specific model.
Auto ML should not replace humans, but work with them. I.e. it is a tool.
This tool can do the following:
1. Auto visualization.
2 Auto feature engineering.
3. Auto backtesting.
4. Auto training (with cost optimization).
5. Hyperparameter optimization.
6. Auto model packaging.
7. Autoload testing and auto security testing.
7. Auto deploy / scale / SLA.
8. Auto monitor.
The goal of AutoML is to save time and reduce risk. I am not sure why you want to do all of the above manually.
Re: Don’t Democratize Data Science
#5So I do not think that this is a black/white situation. I do agree, that any auto ml tool, cannot know what is the correct data sources for a specific use case, nor does it know the business case value of a specific model. Auto ML should not replace humans, but work with them. I.e. it is a tool. This tool can do the following: 1. Auto visualization. 2 Auto feature engineering. 3. Auto backtesting. 4. Auto training (w…
I'm all about AutoML but the best data scientists do what the author says: They try to understand the problem in detail first. I think fewer and fewer do this well.
Re: Don’t Democratize Data Science
#6So I do not think that this is a black/white situation. I do agree, that any auto ml tool, cannot know what is the correct data sources for a specific use case, nor does it know the business case value of a specific model. Auto ML should not replace humans, but work with them. I.e. it is a tool. This tool can do the following: 1. Auto visualization. 2 Auto feature engineering. 3. Auto backtesting. 4. Auto training (w…
I'm all about AutoML but the best data scientists do what the author says: They try to understand the problem in detail first. I think fewer and fewer do this well.
Absolutely, auto ml cannot know your problem, as a word processor cannot know what book you want to write.
The goal of AutoML is to compress the time/money from idea/problem def to running models, it is not to replace the data scientist.