Speaker
Description
The availability of data to astronomers is increasing exponentially every day and a strong synergy between machine learning (ML) algorithms, Big Data and proper computational environment is mandatory. In this context, Cloud Platforms could make a difference allowing to exploit the proper tools of the Data Science while offering the right computational environment for Machine Learning inferences in a BigData fashion just with few clicks. I will review how the Google Cloud Platform could enable astronomers to take the advantages of machine learning (in BigData regime) in an "as-a-service" fashion (MLaaS). I will illustrate the offered tools starting from the data preparation and Data Cleaning (Cloud Dataprep) and off-the shelf machine learning algorithms both for classification and regression problems. The focus of this contribution will be oriented in order to let the people aware of what kind MlaaS services are available and how to exploit them for real astronomer's life problems.
