Bootstrapping an ML Project -- Using Sound to Categorise Fan Failures


Sometimes rather than aim for the grand plan, make something simple and fun to show it works first. Anyone starting a data science project is often excited about the potential and will reach for the stars, before you know it you've a horrendously ambitious and complicated project and you don't know where to start. The result is you never start it because you never get sufficient of the "hooks" done. Note: If you want to get straight to the machine learning project then feel free to skip ahead. Just as you need a fish to bite the hook so you can be a successful fisher, these are things you need to get a bite on before you think you can make a success of something.

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