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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.

Jorge Castanon

IBM
Lead Data Scientist
Bay Area, CA

https://linkedin.com/in/jorgecasta

Jorge Castañón hails from Mexico City and received his Ph.D. in Computational and Applied Mathematics from Rice University. He has a genuine passion for data science and machine learning applications of any kind. Since 2007, he is been developing numerical optimization models and algorithms for regularization and inverse problems. At IBM, Jorge joined the Big Data Analytics team at Silicon Valley Laboratory where he is building the future of machine learning and text analytics tools using Apache Spark and Hadoop.

9:05am PDT

Data and Algorithmic Bias in the Web GardnerRicardo Baeza-Yates

9:50am PDT

Building Word2Vec Models with Text Data AdaJorge Castanon

10:40am PDT

lda2vec AdaChristopher Erick Moody

11:10am PDT

Image Retrieval using Short Texts MarkovMaarten Bosma

11:40am PDT

Using Spark MLlib for NLP MarkovMichelle Casbon

1:40pm PDT

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

2:10pm PDT

Sparse data alternatives with neural network embeddings GardnerMarvin Bertin • David Ott • Mike Tamir

3:00pm PDT

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