Ask HN: What maths are critical to pursuing ML/AI?

Re:Ask HN: What maths are critical to pursuing ML/AI? by samfriedman on Monday August 28, 2017 @01:15PM (#15118255)

There exists a tool called TPOT (Tree-based Pipeline Optimization Tool) [0] that aims to automate the knob-twiddling that tends to go with optimizing Machine Learning models. As these models often have a number of parameters to tune and tweak over large scales, such a tool can be useful to identify performant combinations of these parameters and save time in doing so.

However, many ML practitioners are wary of similar automated ML pipelines, especially as they focus on non-expert users. A huge part of "data science" is the "data" itself. It often has idiosyncrasies and quirks that must be identified and accounted for in any model that hopes to make useful predictions. There are many pitfalls that come from not understanding the base statistical/mathematical assumptions of these tools, and a simplified Automatic ML Suite runs the risk of providing misleading results when used as a one-size-fits-all solution. Even for expert users, such tools often make it difficult (either by mathematical need or software design) to interpret the reasons and causes for their results. "Black boxes" like this are definitely hard to sell up the chain.

[0] https://github.com/rhiever/tpot

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Re:Ask HN: What maths are critical to pursuing ML/AI? by nerdponx on Monday August 28, 2017 @07:16PM (#15120939)

Thanks for clarifying.

These tools do, however, have an important place in saving practitioners time and energy on the "knob-twiddling". It's a little like robot-assisted surgery: the robot doesn't actually do the surgery, but it makes the surgeon's job a whole lot easier.

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Re:Ask HN: What maths are critical to pursuing ML/AI? by Jasamba on Monday August 28, 2017 @10:24PM (#15121676)

That is making the assumption that the person using the tool is a surgeon (an expert in the field who could function independently if needed) which is not who the targeted demographic of such tools is. No-one who understands ML to some non-zero extent would use a plug-and-play ML tool, given that there is ML left to do otherwise. A better analogy would be a janitor activating the red button of the robot machine, which then does its complex surgery where if something goes wrong, the janitor would not be able to replace/understand the problem other than trying to restart it/kick it.

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Re:Ask HN: What maths are critical to pursuing ML/AI? by nerdponx on Wednesday August 30, 2017 @08:02PM (#15137137)

Perhaps, but the meta/hyper-optimization techniques used to implement TPOT, AutoML, etc. are perfectly valid replacements for grid search and stepwise feature selection.

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