Applying AI & Machine Learning To Media, Advertising & Entertainment
SEPTEMBER 22-25
Sponsored by
The data science salon is a unique vertical focused conference which grew into a diverse community of senior data science, machine learning and other technical specialists. We gather face-to-face and virtually to educate each other, illuminate best practices and innovate new solutions in a casual atmosphere.
Featured speakers
KEN ROMANO
Product Director at Associated Press
UPASNA GAUTAM
Product Management at CNN
ILYA KATSOV
Head of Data Science at GridDynamics
ANNE BAUER
Director, Data Science at The New York Times
AMIT BHATTACHARYYA
Head of Data Science at VOX Media
Wes Shockley
Senior Manager, Audience & Analytics at Meredith Corporation
Michael Kaushansky
President of Helia & Chief Data Officer at Havas
Daryl Kang
Lead Data Scientist at Forbes
Manny Neto
VP, Analytics & Data Science at Momentum Worldwide
Alyssa Zeisler
R&D Editor at The Wall Street Journal
ALLY TUBIS
Sr Director of Retention Analytics at Disney Streaming Services
Anu Addanki
Director, Data Science & Engineering at Netflix Studio
Dominick Rocco
Machine Learning Engineer at PhData
RYAN C. MCCABE
Senior Data Scientist at Spotify
Kim Martin
Data Science Manager at Netflix
Bob Bress
Head of Data Science at Freewheel, A Comcast Company
Puneet Gangrade
Data Science Team Lead at MightyHive
Himanshu Swamy
Manager - Data Science at Publicis Sapient
Amy Yu
VP, Product Strategy and Data Science Viacom
Ilke Demir
Senior Research Scientist at Intel Corporation
Nathan Burke
Lead Data Science Engineer at Salesforce
Denver Serrao
Sr. Software Development Engineer at WP Engine
Sophia Tee
Senior Manager, Data Science Verizon
About
Data Science Salon unites the brightest leaders in the media, advertising, and entertainment across the nation in data science fields. We gather face-to-face and virtually to educate each other, illuminate best practices, and innovate new solutions. Data Science Salon | Media, Advertising & Entertainment is the only industry conference that brings together specialists in the media and entertainment data science field to educate each other, illuminate best practices, and innovate new solutions in a casual atmosphere. Get the most current state of current industry trends and innovations in media, advertising, entertainment through DSS podcasts, exclusive content, Webinars and live Trainings. DSS also has an extensive on-demand video library of presentations from the top industry experts.
A SAMPLE OF TOPICS COVERED
Enhancing the Viewer Experience with Machine Learning & AI
Content Personalization and Monetization
Personalization at Scale with AI
Cloud Automation and Machine Learning
Audience Targeting and Segmentation (across platforms)
Data and AI for emerging platforms
Data Governance
and More!
Sessions
(All times are US Eastern Time)
Tuesday, September 22 – Media
12:00 pm – 12:25 pm – Introduction & Guided Meditation
12:25 pm – 12:40 pm – 15 minute break
12:40 pm – 1:10 pm – Data science and fact-based journalism during times of crisis
Ken Romano – Product Director at Associated Press
1:15 pm – 1:45 pm – Sound, Search, and Semantics
Upasna Gautam – Product Management at CNN
1:50 pm – 2:10 pm – Talk by Ilya Katsov, Head of Data Science at GridDynamics
2:10 pm – 2:25 pm – 15 minute break
2:25 pm – 2:55 pm – Experimenting with Recommendations at The New York Times
Anne Bauer – Director of Data Science at The New York Times
3:00 pm – 3:30 pm – Content-Driven Advertising using First Party DataÂ
Amit Bhattacharyya – Head of Data Science at VOX Media
3:35 pm – 4:05 pm – Talk by Anu Addanki, Director, Data Science & Engineering at Netflix Studio
4:05 pm – 4:15 pm – Wrap up
Wednesday, September 23 – Media & Entertainment
11:30 am – 12:30 pm – Virtual Coffee Chat
12:30 pm – 12:40 pm – Introduction & Housekeeping
12:40 pm – 1:10 pm – Changing Media Habits : Data-Driven Editorial Strategy at Meredith
Wes Shockley – Senior Manager – Audience and Analytics at Meredith Corporation
1:15 pm – 1:45 pm – Media Application of Operations Research and Optimization Methods
Bob Bress – Head of Data Science at Freewheel, A Comcast Company
1:50 pm – 2:10 pm – Accelerating big data solutions for media use cases
Steve Sobel – Global Industry Leader – Communications, Media & Entertainment at Databricks
2:10 pm – 2:25 pm – 15 minute break
2:25 pm – 2:55 pm – Summarizing News Clusters Through Text Vectorization
Daryl Kang – Lead Data Scientist at Forbes
3:00 pm – 3:45 pm – Panel Discussion: The Crisis In Media. Facts vs. Fiction in the new Always On World
Sophia Tee – Senior Manager, Data Science at VerizonAlyssa Zeisler – R&D Editor at The Wall Street Journal
Amy Yu – VP, Product Strategy and Data Science at Viacom
3:45 pm – 3:55 pm – Wrap up
5.00 – 5.45 – Cooking Demonstration
Thursday, September 24 – Entertainment
11:30 am – 12:30 pm – Virtual Coffee Chat
12:30 pm – 12:40 pm – Introduction & Housekeeping
12:40 pm – 1:10 pm – Talk by Ally Tubis, Sr Director of Retention Analytics at Disney Streaming Services
1:15 pm – 1:45 pm – Talk TBD
1:50 pm – 2:10 pm – MLOps in Practice: Experiment Tracking & Hyperparameter Tuning
Dominick Rocco – Data Scientist at PhData
2:10 pm – 2:25 pm – 15 minute break
2:25 pm – 2:55 pm – Automated Content Marketing Messaging
Ryan C. McCabe – Senior Data Scientist at Spotify
3:00 pm – 3:30 pm – Interesting applications of data science for Infrastructure in the streaming worldÂ
Kim Martin – Data Science Manager at Netflix
3:35 pm – 4:05 pm – The Future of Filmmaking: AI for Volumetric Capture
Ilke Demir –Â Senior Research Scientist at Intel Corporation
4:05 pm – 4:15 pm – Wrap up
Friday, September 25 – Advertising
11:30 am – 12:30 pm – Virtual Coffee Chat
12:30 pm – 12:40 pm – Introduction & Housekeeping
12:40 pm – 1:10 pm – Attribution Management: What’s Old is New Again
Michael Kaushansk, President at Havas Helia & Chief Data Officer at Havas
1:15 pm – 1:45 pm – Optimizing Media Frequency Using Google Ads Data Hub and Differential Privacy
Puneet Gangrade, Data Science Team Lead at MightyHive
1:50 pm – 2:10 pm – Talk TBD
2:10 pm – 2:25 pm – 15 minute break
2:25 pm – 2:55 pm – Talk by Manny Neto, VP, Analytics & Data Science at Momentum Worldwide
3:00 pm – 3:30 pm – Speeding Audience Segment Discovery with Frequent Pattern Mining
Nathan Burke, Lead Data Science Engineer at Salesforce
3:30 pm – 3:40 pm – Wrap up
Workshops
(All times are US Eastern Time)
Tuesday September 29
12.00 pm – 1.00 pm Managing Serverless Costs with Kubernetes
Denver Serrao – Sr. Software Development Engineer at WP Engine
Serverless has been widely accepted as a mechanism to deploy and run software easily. However, the cost of running production scale workloads on Serverless can be surprisingly high. Wouldn’t it be great if we could get the benefits of running workloads on serverless without the hassle of worrying about costs ?
Enter Knative, an open standard allowing you to run serverless workloads on your own Kubernetes clusters. In this talk, we will walk through a real world example of how we used Google CloudFunctions (FaaS) at WP Engine to deploy a serverless data pipeline, and then transitioned that workload to using Cloud Run (built upon Knative) and Kubernetes to achieve the same results at a greatly reduced cost. We will dive deep into how we achieved the cost savings, handle fault tolerance, concurrency and auto-scaling
Now our developers can focus on code instead of the plumbing of managing infrastructure, while delivering customer and business value quickly and easily.
Wednesday September 30
12.00 pm – 1.00 pm Spark NLP for Data Scientists
Presented by John Snow Labs
Thursday October 1
12.00 pm – 2.00 pm Optimize content at scale using State-of-Art NLP techniques in cloud environment
Himanshu Swamy – Manager Data Science at Publicis Sapient
NLP, also known as computational linguistics, is the combination of AI and linguistics that allows us to talk to machines as if they were human. This session is about an important concept used in the current state of the art applications in Speech Recognition and Natural Language Processing – viz Sequence to Sequence modelling. This will convert an input sequence into an output sequence. Just to give you a sneak peek of the potential application of seq2seq model can be speech recognition, machine translation, question answering, Neural Machine Translation (NMT), and image caption generation. This workshop will showcase on how to build a language model that we’ll focus on using recurrent neural network which captures the entire context of the input sequence. Seq2seq models typically employ two Recurring Neural Networks (RNNs). The model is trained to map an input sequence to an output sequence which are not necessarily of the same length as each other. The basic structure of the model is a network of encoders and decoder, bidirectional self-attention layer. I will showcase thorough implementation of a content optimization system using NLP techniques along with scalable deployment of model within Cloud.
Register
For any queries regarding Registration or Tickets, please contact us via info@formulated.byÂ