Researcher tackles some of the biggest bottlenecks holding back the data science industry
Wednesday, February 25, 2015 - 09:00
in Mathematics & Economics
When Kalyan Veeramachaneni joined the Any Scale Learning For All (ALFA) group at MIT's CSAIL as a postdoc in 2010, he worked on large-scale machine-learning platforms that enable the construction of models from huge data sets. "The question then was how to decompose a learning algorithm and data into pieces, so each piece could be locally loaded into different machines and several models could be learnt independently," says Veeramachaneni, currently a research scientist at ALFA.