Azure Machine Learning is an integrated, end-to- data data science experience designed for professionals to prepare data and create, manage and deploy machine learning models at any scale.Azure Machine Learning was developed with the conviction that the scale of the problem you are trying to solve shouldn’t matter, that integrating Spark into your regular workflow shouldn’t present any barriers and that you, the professional data scientist, should be able to focus on
solving machine learning problems, rather than software engineering problems.
In this session, we demonstrate the power of Apache Spark on Azure Machine Learning by training a model on a variety of targets at the switch of a button, tracking the history of the model and operationalizing it − all in just under 15 minutes.
Miruna Oprescu is a Software Engineer at Microsoft specializing in tools and infrastructure for big data and machine learning. Her goal is to make machine learning simple for both developers and end users. As an active MMLSpark (Microsoft Machine Learning for Spark) contributor, she has been working on Python/R wrapper generation for Spark pipeline stages and a robust testing framework for Spark pipelines using Jupyter Notebooks.