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Ameet Talwalkar

Ameet Talwalkar
Assistant Professor | Cofounder and Chief Scientist, Carnegie Mellon University | Determined AI

Website

Ameet Talwalkar is an NSF post-doctoral fellow in the Computer Science Division at UC Berkeley. His work focuses on devising scalable machine learning algorithms, and more recently, on interdisciplinary approaches for connecting advances in machine learning to large-scale problems in science and technology. He obtained a bachelor’s degree from Yale University and a Ph.D. from the Courant Institute at New York University.

Sessions

Hadoop and Beyond
GA Ballroom K
Tutorial Please note: to attend, your registration must include Tutorials on Tuesday.
Sameer Agarwal (UC Berkeley), Tathagata Das (Databricks), Ali Ghodsi (UC Berkeley), Ion Stoica (UC Berkeley), Ameet Talwalkar (Carnegie Mellon University | Determined AI), Reynold Xin (Databricks), Matei Zaharia (Databricks), Joseph Gonzalez (UC Berkeley)
Average rating: ****.
(4.29, 7 ratings)
3-Hours: An introduction to the newest components of the open-source Berkeley Data Analytics Stack (BDAS) in development at UC Berkeley (and an overview of existing ones). BlinkDB is a SQL engine that provides fast approximate distributed query results. MLbase includes a library to make machine learning at scale easy. Tachyon is a file system that provides memory speed sharing across frameworks.. Read more.
Hadoop and Beyond
GA Ballroom K
Tutorial Please note: to attend, your registration must include Tutorials on Tuesday.
Andy Konwinski (Databricks), Sameer Agarwal (UC Berkeley), Tathagata Das (Databricks), Ameet Talwalkar (Carnegie Mellon University | Determined AI), Shivaram Venkataraman (UC Berkeley), Patrick Wendell (Databricks), Reynold Xin (Databricks), Matei Zaharia (Databricks), Joseph Gonzalez (UC Berkeley), Haoyuan Li (Alluxio)
Average rating: ***..
(3.10, 10 ratings)
3-Hours: Get hands-on training with the newest components of the open-source Berkeley Data Analytics Stack (BDAS). Lessons will cover BlinkDB, MLbase, Spark, Spark Streaming, and Shark. We will provide each audience member with an EC2 cluster and walk through hands-on exercises using these technologies to analyze real-world datasets. Read more.
Data Science
Ballroom AB
Ameet Talwalkar (Carnegie Mellon University | Determined AI), Evan Sparks (Determined AI)
Average rating: ****.
(4.14, 7 ratings)
Implementing and consuming Machine Learning techniques at scale are difficult tasks for ML Developers and End Users. MLbase (www.mlbase.org) is an open-source platform under active development addressing the issues of both groups. In this talk we will describe the high-level functionality of MLbase and demonstrate its *scalability* and *ease-of-use* via real-world examples. Read more.