Sep 23–26, 2019

Schedule: Retail and e-commerce sessions

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9:00am - 5:00pm Monday, September 23 & Tuesday, September 24
Location: 1A 03
Bargava Subramanian (Binaize Labs), Amit Kapoor (narrativeVIZ)
In this two-days workshop, you will learn the different paradigms of recommendation systems and get introduced to the usage of deep-learning based approaches . By the end of the workshop, you will have enough practical hands-on knowledge to build, select, deploy and maintain a recommendation system for your problem. Read more.
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11:20am12:00pm Wednesday, September 25, 2019
Location: 1A 15/16
Navinder Pal Singh Brar (Walmart Labs)
Each week 275 million people shop at Walmart, generating multi-terabytes of interaction and transaction data. In Customer Backbone team, we enable extraction, transforming and storing of customer data to be served to teams such as Ads and Personalisation. At 5 Billion events/day our Kafka Streams cluster processes events from various channels and maintains a uniform identity of a customer. Read more.
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1:15pm1:55pm Wednesday, September 25, 2019
Location: 1A 08/10
James Tang (WalmartLabs), Yiyi Zeng (WalmartLabs), Linhong Kang (WalmartLabs)
How No1 retailer provides secure and seamless shopping experience through machine learning and large scale data analysis on centralized platform. Read more.
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2:05pm2:45pm Wednesday, September 25, 2019
Location: 1A 12/14
Mikio Braun (Zalando SE)
With ML becoming more and more mainstream, the side effects of using machine learning and AI on our lives become more and more visible. One has to take extra measures to make machine learning models fair and unbiased In addition, awareness for preserving the privacy in ML models is rapidly growing. Read more.
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2:55pm3:35pm Wednesday, September 25, 2019
Location: 1A 08/10
Fei Wang (CarGurus), Michael Brautbar (CarGurus)
This session will present the case study for the CarGurus TV Attribution Model. Attendees will learn how the creation of a causal inference model can be leveraged to calculate cost per acquisition (CPA) of TV spend and measure effectiveness when compared to CPA of Digital Performance Marketing spend. Read more.
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4:35pm5:15pm Wednesday, September 25, 2019
Location: 1A 08/10
Robert Pesch (inovex GmbH), Robin Senge (inovex GmbH)
In this talk, we outline the development process, the statistical modeling, the data-driven decision making, and the components needed for productionizing a fully automated and highly scalable demand forecasting system for an online grocery shop for a billion-dollar retail group in Europe. Read more.
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5:25pm6:05pm Wednesday, September 25, 2019
Location: 1A 12/14
Subhasish Misra (Walmart )
Causal questions are ubiquitous. Randomized tests are considered to be the gold standard for these. However, such tests are not always feasible and then, one just has observational data to get to causal insights. Techniques such as matching offer a solve then. This talk will offer a take on the above aspects, plus share practical tips when trying to infer causal effects. Read more.
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11:20am12:00pm Thursday, September 26, 2019
Location: 3B - Expo Hall
Brian Keng (Rubikloud Technologies Inc)
Automating decisions require a system to consider more than just a data-driven prediction. Real-world decisions require additional constraints and fuzzy objectives to ensure that they are robust and consistent with business goals. This talk will describe how to leverage modern machine learning methods and traditional mathematical optimization techniques for decision automation. Read more.
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2:05pm2:45pm Thursday, September 26, 2019
Location: 1A 15/16
Karthik Ramasamy (Streamlio), Anand Madhavan (Narvar)
Narvar provides next generation post transaction experience for over 500+ retailers. This talk explores the journey of how Narvar moving away from using a slew of technologies for their platform and consolidating their use cases using Apache Pulsar. Read more.
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4:35pm5:15pm Thursday, September 26, 2019
Location: 1A 15/16
Neelesh Salian (Stitch Fix)
It is important to understand why Data Lineage is needed for an organization. Once the purpose is defined, we can talk about how to go about building such a system. Read more.

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