Writing good instructions to achieve high precision and throughput.
End of week debrief, weekly business review, monthly learning sessions, and quarter review.
Pilot & copilot, literature review, methodology review, and timeboxing.
15 minutes a week to document your work, increase visibility, and earn trust.
Mindset, 100-day plan, and balancing learning and taking action to earn trust.
Ever revisit a project & replicate the results the first time round? Me neither. Thus I adopted these habits.
It's not enough to have a good strategy and plan. Execution is just as important.
Haste makes waste. Diving into a data science problem may not be the fastest route to getting it done.
Initially, I didn't like it. But over time, it grew on me. Here's why.
Taking the best from agile and modifying it to fit the data science process (Part 2 of 2).
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