APPLYING AI & MACHINE LEARNING
TO MEDIA AND ENTERTAINMENT

LOS ANGELES, DECEMBER 14 2017

The Data Science Salon is a destination conference which brings together specialists face-to-face to educate each other, illuminate best practices, and innovate new solutions in a casual atmosphere with food, drinks, and entertainment.

Data Science Salon unites the brightest leaders in the media and entertainment in Los Angeles data science fields. We gather to educate each other, illuminate best practices, and innovate new solutions. Data Science Salon | LA is a one day conference with workshops for executives, data scientists, developers, and business development professionals alike. We’ve collected extensive data to figure out just the right mix of people, content, and entertainment to make our conferences as seamless, informative, and fun as possible.

Raise your profile and establish thought leadership for your business. Join the most influential leaders in data science and share your knowledge about the latest machine learning techniques and interesting case studies. Data Science Salon will bring together twenty speakers per event. With a full day of diverse content there’s plenty of opportunities to share your knowledge, attract new hires and make lifelong business connections.

SPEAKERS

DAY

ENTERTAINERS

ATTENDEES

Keynote speakers

Meet our speakers

Jonathan Morra

Vice President, Data Science at ZEFR

Kevin Perko

Data Science Lead at Scribd

Ann Greenberg

Founder & CEO, Entertainment AI™

Becky Tucker

Senior Data Scientist at Netflix

Xavier Kochhar

Founder, The Video Genome Project

Gwen Miller

Vice President, Audience & Platforms at Kin Community

Schedule

9:00 AM - 9:55 AM
Coffee & Registration

Come early and get a book of your choice from O'Reilly Media (first come first serve)

Anna Anisin Founder and CEO at Formulatedby

Xavier Kochhar (Founder The Video Genome Project, Hulu)

I'll cover our experience using deep learning, going from scratch to deploying models in production to improve the product experience. I'll go in-depth in terms of how we started deep learning from scratch, including navigating the maze of frameworks and hyper-parameters to optimize. I'll discuss pitfalls of using other people's algorithms and make a call for more rigor in publishing data science blog posts. I'll close with how our failure turned into an open source contribution and the work in moving from dev to production.

Data Science Lead at Scribd

Becky Tucker, Senior Data Scientist , Netflix

Mostafa Majidpour, Senior Data Scientist, TIME, Inc.

Joe Devon (Moderator) Founding Partner atDiamond sits down with: Alejandro Cantarero VP, Data at tronc (formely Tribune Publishing), Keisuke Inoue VP Data Science at Emogi, Gwen Miller, Vice President, Audience & Platforms at Kin Community, Hollie Choi, Executive Director, IT Intellectual Property Management at 20th Century Fox. For a deep conversation about Data Science Applications in Media and Entertainment.

Alejandro Cantarero VP, Data at Tribune Publishing, Keisuke Inoue VP Data Science at Emogi, Gwen Miller, VP, Audience & Platforms at Kin Community, Hollie Choi, Executive Director, IT Intellectual Property Management at 20th Century Fox

Vice President, Data Science at ZEFR

Zahra Ferdowsi (Data Scientist, Snapchat)

Within marketing research, big data is often described as being “census” data for the population that it represents. The devil is in the details and when we take a closer look we can see that this isn’t the case. There are many situations that are not captured within the population that big data purports to be a census of. Big data isn’t even a census of itself since it’s not uncommon for records to be excluded either by accident during the collection process or by design in the cleaning processor. Unfortunately, our industry is so enamored with the size of big data that some users of data are willing to trade off precision for tonnage. Fortunately, if the shortcomings of big data are understood and corrected it can accurately represent the population that it measures in the correct proportion to the universe. We will discuss a method that Nielsen has developed called “Common Homes” that is designed to identify and correct the shortcomings of big data sets that represent media consumption.

Daniel Monistere (SVP – Client Solutions, Nielsen)

Expect a special suprise during this break =)

Ann E. Greenberg, Founder & CEO at Entertainment AI™

Recent advances in deep learning have fueled tremendous excitement about the potential for artificial intelligence to solve countless problems. But there are some perils and pitfalls endemic to these new techniques, particularly because they ignore two essential components of the scientific method: (1) understanding the how; and (2) explaining the why. Dr. Michael Housman offers up a two specific examples from his own career as a data scientist to show how a naive application of deep learning algorithms can lead data scientists to the wrong conclusion and offers up some guidance for avoiding these mistakes.

Michael Hausman (Co-Founder and Chief Data Science Officer, RapportBoostAI)

Ali Baghshomali, Data Scientist at Buzzfeed

Joao Fiadeiro, Quantitative Data Analyst at YouTube

Mollie Pettit, Data Scientist at Metis

Stick around for more networking accompanied by artisanal pizza, beer and wine and LIVE Entertainment!

Event tickets

Hurry up and get your tickets prices go up on November 15th

Individual
$279
  • Regular Seating
  • Food Included
  • Happy Hour
Register
Student
$109
  • Regular Seating
  • Food Included
  • Happy Hour
Register

WHAT PEOPLE ARE SAYING

The Data Science Salon series is the most important new conversation happening in the industry right now.
Eduardo Arino de la RubiaDomino Data Lab
What I appreciate about the Data Science Salon is that it’s a conference I actually want to go to – it’s fun, you learn some great things, you meet some great people, and at the end of the day you feel energized rather than drained. It’s taken me out of my silo and put me in the community. I think it’s great.
Jack PalmerPlotly
Their conferences are smaller, more intimate, with lots of opportunities for workshops and networking, which helps fill that need in the data science community to get together from time to time.
Roger MagoulasO'Reilly Media

sponsors

Location

  • General Assembly Downtown LA, 360 E 2nd St, Los Angeles
  • info@formulated.by
  • (415) 322-0760
  • December 14, 2017
  • 9:30 AM – 8:00 PM