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Machine learning needs information to mold its utility.
In response, machine learning needs to reinvent itself for big data processing.
Although machine learning needs human input to start, it will eventually reach a point when it will outsmart us.
Even with a core team of engineers, machine learning needs to be easy to access for employees in far out areas of a corporation.
This is something that every startup using any amount of machine learning needs to consider building into their products and platforms in a way that informs users how their data is being parsed but without giving away any secret sauce.
Similar(55)
Statistical machine learning models need, however, input variable previously acquired datasets.
"If you do machine learning, you need to have a lot of data to train your algorithm.
However, the machine learning algorithms need to be evaluated in the case where wells contain a large number of wireline logs which are highly-sampled.
Machine Learning algorithms need to be limited by time in order to ingest data in sizes which can be processed meaningfully.
Because data sets often contain tens of thousands of compounds and the size of available data sets is expected to grow rapidly, the machine learning algorithms need to be highly numerically efficient.
This tends to be the exception rather than the rule, however, which means most machine learning startups need to look to partnerships or large customers to achieve defensibility and scale.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com