ND4J: A scientific computing framework for the JVM

In this talk, we present the ND4J framework with an iScala notebook. Combined with Spark's dataframes, this is making real data science viable in Scala. ND4J is "Numpy for Java." It works with multiple architectures (or backends) that allow for run-time-neutral scientific computing as well as chip-specific optimizations -- all while writing the same code. Algorithm developers and scientific engineers can write code for a Spark, Hadoop, or Flink cluster while keeping underlying computations that are platform-agnostic. A modern runtime for the JVM with the capability to work with GPUs lets engineers leverage the best parts of the production ecosystem without having to pick which scientific library to use. ABOUT DATA COUNCIL: Data Council (https://www.datacouncil.ai/) is a community and conference series that provides data professionals with the learning and networking opportunities they need to grow their careers. Make sure to subscribe to our channel for more videos, including DC_THURS, our series of live online interviews with leading data professionals from top open source projects and startups. FOLLOW DATA COUNCIL: Twitter: https://twitter.com/DataCouncilAI LinkedIn: https://www.linkedin.com/company/datacouncil-ai Facebook: https://www.facebook.com/datacouncilai Eventbrite: https://www.eventbrite.com/o/data-council-30357384520