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.

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Did we miss anything? Is there something you would like to see in depth in the next articles?

I hope you enjoy it!