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Hi everyone, one of our writers wrote an article on FloydHub blog that aims to give a checklist which a machine learning practitioner can refer from time-to-time in his own projects. The article tries to combine the pieces of advice collected from practitioners like Andrej Karpathy, Josh Tobin and at the same time includes many experiences.
Did we miss anything? Is there something you would like to see in depth in the next articles?
I hope you enjoy it!
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