Apache: Big Data North America 2017

 A serious issue when developing distributed machine learning algorithms is the lack of people who understand the mathematics, distributed data, AND have free time. Further, most distributed engines have APIs that were not designed to be mathematically expressive, implementations are hard to follow; another qualified person must review. The Mahout project has spent two years building modular system bindings for distributed engines such as Apache Spark and Apache Flink, native solvers to enable CPU/GPU acceleration, an abstracted R-Like Scala DSL for tensor algebra on distributed matrices, and a consistent API to implement distributed algorithms. This creates an extendable and new-contributor friendly framework for machine learning. We’ll also discuss the project vision for creating a CRAN like repository of user contributed algorithms and how we are evangelizing this vision.    Mail Merge Schedule ABD submissions ABD proposals from AC Stuff that doesn't belong to ABD Mail Merge Logs  Explore A serious issue when developing distributed machine learning algorithms is the lack of people who understand the mathematics, distributed data, AND have free time. Further, most distributed engines have APIs that were not designed to be mathematically expressive, implementations are hard to follow; another qualified person must review. The Mahout project has spent two years building modular system bindings for distributed engines such as Apache Spark and Apache Flink, native solvers to enable CPU/GPU acceleration, an abstracted R-Like Scala DSL for tensor algebra on distributed matrices, and a consistent API to implement distributed algorithms. This creates an extendable and new-contributor friendly framework for machine learning. We’ll also discuss the project vision for creating a CRAN like repository of user contributed algorithms and how we are evangelizing this vision.