This talk will be about walking through the steps to put a TensorFlow project into production on the web with Flask and Heroku. The goal is to introduce the project and show how TensorFlow can be used online for real data tasks, and discuss other considerations for deployment of a TensorFlow project. Abstract TensorFlow is a deep learning library with Python and C++ bindings that was released in 2015. The talk start with a brief intro to TensorFlow, and then dive into the specific steps to set up a simple project that can be served online.
Bio: Kendall is a lead software engineer at YesGraph, where he uses machine learning and Flask to power better invite flows for mobile and web apps. Previously he worked as an independent software consultant for four years, and before that he was a hardware designer at Qualcomm in San Diego for three years. Kendall was an an organizer of the San Diego Python Users Group, where he helped plan six one-day workshops on various Python topics. Bio2 David Clark has a background in astrophysics, where he used Python extensively to analyze astronomical data. He recently transitioned careers to data science. Currently he is doing consulting for two startups. At Palo Alto Scientific, Inc., he uses the machine learning library TensorFlow to model sensor data from a wearable and infer a runner’s performance. He is also doing work for Quantea, Inc., making a dashboard using the Python libraries Bokeh and Pandas.