Using Python at Scale for Data Science - Wes McKinney While Python is a de-fac

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Agenda:
6:00p - 6:30p / Network & refreshments
6:30p - 8:00p / Speaker time

Using Python at Scale for Data Science - Wes McKinney

While Python is a de-facto language for modern data engineering and data science, Python development has been confined to local data processing—thereby limiting its users to smaller data sets. Historically, to address bigger data workloads, Python developers have had to extract samples or aggregates, forcing compromises in data fidelity, adding ETL costs, and ultimately leading to a loss of productivity and addressable use cases.

Ibis, a new open source data analytics framework for Python developers, has the goal of enabling the Python data ecosystem (NumPy, pandas, etc.) to operate efficiently at Hadoop scale. To enable high performance Python at scale without the age-old JVM interoperability problems, Ibis take advantage of unique synergies between Python and Impala, the leading open source MPP analytical query engine. In this talk, Ibis creator Wes McKinney, who was also the creator of pandas, will demo the current capabilities of Ibis as well as explain its roadmap.

Repurposing Existing Deep Learning Models: Image Similarity for fun (& profit?)

Hear how one data scientist spent an afternoon exploiting an existing trained deep learning model, extracting deep features, and transferring them in order to build an image-based similarity service for photographs of houses.

Rajat Arya will show you don't need to be an expert in deep learning or convolutional neural networks in order to leverage deep features in your next application.

The presentation will be entirely delivered from an IPython Notebook and written in Python, using Dato for extracting deep features from a trained deep learning model and deploying the image similarity service.

After a dozen years of building scalable systems at AWS, Microsoft, AddThis, and Dato, Rajat recently started working more closely with data scientists, helping them build intelligent applications using Dato.