Hi all, In our daily workings with Python and its powerful libraries in the Data Science domain (among others), it's easy to understand why we intuitively believe adages like - "More data is good", "The more, the better" etc, because, for the most part, they do help in solving problems more accurately by considering larger representative data - the kind of representation that is possible just by virtue of the sheer quantity of it.
Today's public (& free) lecture conducted by Hasgeek <https://hasgeek.com> however, is titled - *The big data paradox: how a company like Mozilla is focussing on better data, not more <https://hasgeek.com/lean-data-practices/the-big-data-paradox-public-lecture/#>* -where Stan Leong, Dr. Rebecca Weiss and Urmkia - Mika - Devi Shah from Mozilla's senior Leadership will be sharing their experiences about creating first-class products that don’t compromise personal data and focus instead on what matters: function, performance, engagement, and trust. This is an intriguing premise and I think it'd benefit you to attend as well, if you're working even remotely with data (big or small :) ) More details about the event - https://hasgeek.com/lean-data-practices/the-big-data-paradox-public-lecture/# *When?* Today - 9th Oct , 5.45 PM - 8 PM *Where?* Bangalore International Centre (BIC), Domlur Map : https://goo.gl/maps/hACDP8Ftkjb8Bfej7 *If you're unable to attend it offline, they'll be livestreaming it as well at - https://hasgeek.tv <https://hasgeek.tv>* Thanks Abhiram R <https://abhiramr.com> (Co-organiser - Bangpypers) _______________________________________________ BangPypers mailing list BangPypers@python.org https://mail.python.org/mailman/listinfo/bangpypers
