Distributed Machine Learning with Python
Speaker: Brad Miro
As the amount of data continues to grow, the need for distributed machine learning continues to grows with it. We’ll discuss techniques and methods for distributing machine learning training such as data parallelism and model parallelism. We’ll then discuss how to build scalable machine learning systems and show two examples of this using Python: one with Apache Spark MLlib, one with TensorFlow.