Slides can be found here: slideshare.net/PyData/wiseio-pydatasv13-slides
At wise.io we are building a machine-learning platform that makes efficient and accurate learning algorithms available in an easy-to-use service. In this presentation, I will describe how the platform works and how we're using Python to make it scalable and accessible.
Machine-learning is an active field of data science, where sophisticated models are "trained" on data and used to enable human-like cognition in data analysis pipelines and data-heavy applications. Data scientists need the most efficient and most accurate machine-learning implementations, while developers need on-ramps that make it easy to incorporate machine-learning into their applications.
Highlights of our platform include one-step data ingestion and model building, validation, hosting, integration and sharing. A domain intelligence "marketplace" enables domain-specific knowledge to be incorporated in a model with a click (or a "git push") and is scaled automatically to handle large datasets. We use Python and a range of cloud and data frameworks to make this possible, including Anaconda, PiCloud, Pandas and PyTables.