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Data By the Bay

Data By the Bay is the first Data Grid conference matrix with 6 vertical application areas spanned by multiple horizontal data pipelines, platforms, and algorithms. We are unifying data science and data engineering, showing what really works to run businesses at scale.

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9:50am

Elastic Data Pipelines AdaSunil • Claudio Caldato • Adam Mollenkopf

10:40am

Deploying Image Recognition on a Budget AdaShourabh Rawat

11:10am

Investing in Data Analytics: Risks and Opportunities in the Zettabyte Era AdaKanu Gulati

11:40am

Apache Flink: A Very Quick Guide AdaVladimir Bacvanski

1:10pm

Akka Streams for Large Scale Data Processing AdaZack Loebel-Begelman • Dustin Lyons

2:10pm

Twitter Heron in Practice AdaKarthik Ramasamy

3:00pm

A Real Time Analytics Framework AdaHiral Patel

4:00pm

Quantitative Trading with Machine Learning AdaMartin Froehler

9:50am

Building Word2Vec Models with Text Data AdaJorge Castanon

10:40am

lda2vec AdaChristopher Erick Moody

11:40am

Automatic Links for a Web of Text AdaScott (TS) Waterman

1:10pm

An Innovative Approach to Labeling Ground Truth in Speech AdaJill Desmond

1:40pm

Of Rules and Probabilities: Computational Linguistics Methods for Improving Machine Learning Models AdaVita Markman

2:10pm

Aspect Based Sentiment Analysis in 20+ Languages AdaAntonio Valderrabanos

3:00pm

Alluxio (formerly Tachyon): Open Source Memory Speed Virtual Distributed Storage System AdaGene Pang

4:00pm

Mining Noisy Transaction Data with Neural Nets AdaFrank Taylor

9:50am

Synthesizing human and machine capabilities AdaEric Colson

10:10am

Data From Click To Settlement: A Full-Funnel UX Approach AdaMichael Terry

10:40am

End-2-End Monitoring and Troubleshooting a Real-Time Data Pipeline AdaAlan Ngai

11:10am

Creating Value by Turning Law Into Data AdaDaniel Lewis

11:40am

Hidden in plain sight: Using law to summarize the law AdaRichard Downe

1:10pm

Case Law and ML on Spark AdaJeremy Corbett

1:40pm

Making Predictions Under Lending Regulations AdaYujay Huoh

2:10pm

Building a Graph of all US businesses using Spark technologies AdaAlexis Roos

2:30pm

Building AI that Searches and Sells AdaAnand Kulkarni

3:00pm

Analyzing Time Interval Data AdaPhilipp Meisen

4:00pm

Deep Dive: Spark Memory Management AdaAndrew Or

9:50am

Beyond 1M Acres of Drone Imagery AdaNicholas Pilkington

10:40am

Predicting Hacker News with Beam and TensorFlow AdaEric Anderson

11:10am

Know the air you are breathing AdaSeema Jethani

11:40am

Recommendations for Building Machine Learning Software AdaJustin Basilico

1:10pm

Building realtime efficient queries and batch jobs in an IOT platform AdaDinesh Narayanan

2:10pm

Deep dive and best practices of Spark streaming AdaPrakash Chockalingam

3:00pm

Hidden GEMMs: How Optimized Math Libraries Work AdaMarek Kolodziej

4:00pm

Apache Beam (incubating): Unified batch and streaming data processing AdaEugene Kirpichov

4:20pm

Data in the Apache "big data" ecosystem AdaKonstantin Boudnik

9:50am

On the path to data Nirvana: Supporting OLTP and OLAP on Hadoop AdaMonte Zweben

10:40am

Real Time Machine Learning Visualization with Spark AdaChester Chen

11:10am

A Scalable GA4GH Server Implementation AdaAndy Petrella

11:40am

Interactive Machine Learning on Genomics Data with the Spark Notebook AdaAndy Petrella

12:00pm

Challeneges in 3D Volumetric Data Sets AdaTodd Huffman

1:10pm

Designing for Inconsistency AdaBrian Studwell

1:40pm

How to Use Big Data to Inspire Consumer Confidence AdaDaniel Doerr

2:10pm

The UMLS - Authoritative biomedical concept names in context AdaBrian Carlsen • Mark Samuel Tuttle

3:00pm

Data Design Challenges for Enterprise IoT Applications: Semantic Sensor Network Ontologies AdaZachary Taschdjian

3:30pm

How Data helps UX evolves at realtor.com AdaIan Lin

4:00pm

Deep Learning, Heart Rate Sensors, and Strokes AdaBrandon Ballinger • Johnson Hsieh

4:50pm

Towards a virtual reality meta-Earth AdaBo Huang