Data Science Gambling

• Data Science Gambling Games

A data science blog by Mitch Gaiser. If you or someone you know has a gambling problem. Please call 1-800-GAMBLER. ©2020 by Bettor Picks. All trademarks are. The global online gambling market is anticipated to be valued at more than $94 billion in 2024, and increasing use of more advanced data science, machine learning, and AI techniques to improve the online gambling experience will most certainly play a role in this market growth. The first people to adopt big data in the gambling world were the bookmakers - those that live by the odds they establish. Getting as much information as possible is a crucial aspect of the business, so the moment new techniques designed to analyze and transmit that data cropped up, adopting it was a simple decision to make.

This week, Hugo speaks with Marco Blume, Trading Director at Pinnacle Sports. Marco and Hugo will talk about the role of data science in large-scale bets and bookmaking, how Marco is training an army of data scientists and much more. At Pinnacle, Marco uses tight risk-management built on cutting-edge models to provide bets not only on sports but on questions such as who will be the next pope? Who will be the world hot dog eating champion, who will land on mars first and who will be on the iron throne at the end of game of thrones. They’ll discuss the relations between risk management and uncertainty, how great forecasters are necessarily good at updating their predictions in the light of new data and evidence, how you can model this using Bayesian inference and the future of biometric sensing in sports betting. And, as always, much, much more.This is the DataCamp podcast link and check it out for the show notes and other goodies: https://www.datacamp.com/community/podcast/data-science-gambling-bookmaking?utm_source=soundcloud&utm_medium=social&utm_campaign=podcast_53

Genre

Science

Comment by Sushrut

51:03 Now we know Bran Stark is the one!!

Comment by Kareem Alaraby

did Justin record those segments about distribution's storie's ? if so can you provide a link ?

Comment by DataFramed

@crist-bal-j-correa-r: Hey, we suggest taking our intro courses depending on what language you prefer. Intro to SQL(https://www.datacamp.com/courses/intro-to-sql-for-data-science), our Tidyverse Fundamentals with R Track(https://www.datacamp.com/tracks/tidyverse-fundamentals), and finally for Python, our Introduction to Data Science in Python course(https://www.datacamp.com/courses/introduction-to-data-science-in-python).

Comment by correacristobal

Data Science Gambling Games

Hey! Thank you for sharing this. I've been a DC member for over three years now and still haven't taken any course, but I've been working in the gambling industry for longer and this podcast inspired me to start learning. Where would you say a non-programmer should start if they're looking to learn all of this? From 0 to building a proper data lake house to pull several live datapoints and have them analyzed and weighed? :D