This is a note quoted from ‘Mastering Machine Learning with Python in Six Steps’ by data scientist Manohar 1. Beautiful is better than ugly — be consistent. 2. Complex is better than complicated — use existing libraries. 3. Simple is better than complex — keep it simple and stupid (KISS). 4. Flat is better than nested — avoid nested ifs. 5. Explicit is better than implicit — be clear. 6. Sparse is better than dense — separate code into modules. 7. Readability counts — indenting for easy readability. 8. Special cases aren’t special enough to break the rules — everything is an object. 9. Errors should never pass silently — good exception handler. 10. Although practicality beats purity — if required, break the rules. 11. Unless explicitly silenced — error logging and traceability. 12. In ambiguity, refuse the temptation to guess — Python syntax is simpler; however, many times we might take a longer time to decipher it. 13. Although that way may not be obvious at first unless you’re Dutch — there is not only one of way of achieving something. 14. There should be preferably only one obvious way to do it — use existing libraries. 15. If the implementation is hard to explain, it’s a bad idea — if you can’t explain in simple terms then you don’t understand it well enough. 16. Now is better than never — there are quick/dirty ways to get the job done rather than trying too much to optimize. 17. Although never is often better than *right* now — although there is a quick/dirty way, don’t head in the path that will not allow a graceful way back. 18. Namespaces are one honking great idea, so let’s do more of those! — be specific. 19. If the implementation is easy to explain, it may be a good idea — simplicity. Reference: — https://www.amazon.com/Mastering-Machine-Learning-Python-Steps/dp/1484228650
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