Octury deep sparkle 2 how to#
Octury deep sparkle 2 full#

Read the full podcast episode summary here. Join us for one of our upcoming events: _ Thank you to you our sponsor, _Talent Insights Group_! Tune in for in-depth insights into this, and more, with Mia OвЂ™Dell. вЂњBut for something that isnвЂ™t necessarily core to the business, ML Ops can result in putting far too much effort on the defensive side, and not enough yet on the offensive side.вЂќ вЂњIf your first machine learning model is something thatвЂ™s extremely critical to the success of the business, of course you want to over invest in its reliance,вЂќ she says. ItвЂ™s also important to understand where and when ML Ops becomes important to a business, OвЂ™Dell adds, saying that a lot of organisations make the mistake of going all-out when theyвЂ™re just at the start of the journey, where the value of ML Ops will be marginal and difficult to articulate.

Success depends on being able to work with the teams to come up with a strong and compelling vision.ДЇinally, OвЂ™Dell also shares her concept of вЂњmachine learning offenseвЂќ and вЂњmachine learning defenceвЂќ as a way to help articulate the value of ML Ops at a time where non-data executives within enterprises are still struggling to understand the breakdown and operation of ML Ops teams. ThereвЂ™s no вЂњone size fits allвЂќ approach, she says.

Octury deep sparkle 2 how to#

OвЂ™Dell вЂ“ who was also responsible for scaling the data practice in a previous organisation вЂ“ also shares some insights about how to approach data scaling. Sportsbet is also growing its data practice and looking to nearly double its team sizes by the end of the year. This week on the Data Futurology podcast, Mia OвЂ™Dell, the GM of Data Science at Sportsbet, kicks thing off by explaining how the company brings together three separate data teams, across three lines of business, to achieve meaningful and collaborative data outcomes.

Online wagering is one of the most sophisticated and complex fields for data and analytics.