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machinelearning

#machinelearning

Anon Ymous

Mon Feb 24 16:27:25 2020
<773ab1f1> Alright so machinelearning is a use case playground
<773ab1f1> and just like blockchain, 95% of it is bullshit
<773ab1f1> <https://www.jeremyjordan.me/ml-requirements/> This will help you define the iteration process
— Building machine learning products: a problem well-defined is a problem half-solved.
— Previously, I wrote about organizing machine learning projects where I presented the framework that I use for building and deploying models. However, that framework operates on the implicit assumption that you already know generally what your model should do. In this post, we’ll dig deeper into how to develop the
<773ab1f1> If you like that, more meat is here: <http://martin.zinkevich.org/rules_of_ml/rules_of_ml.pdf>
<773ab1f1> What you run into, and you run into this a lot in cyber too are ‘silver bullet solutions’
<773ab1f1> this can be defined by the following matrix
<773ab1f1>


<773ab1f1> Silver bullets appear when the seller doesn’t know how to solve a problem and a buyer doesn’t know how to solve a problem.
<773ab1f1> Its a question of information asymmetry
<d666283b> <@U4FQ46RGU> quality content
<773ab1f1> Cheers buddy, its my pleasure
<773ab1f1> Fact of the matter is, a SHITTON of money is changing hands where no one properly understands the problem being solved
<773ab1f1> That defcon talk I posted a few posts back up is bomb as fuck and suppppper thiccccc. You gotta pause it to process all the information though. That guy is a research beast

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