Friday 1:15 PM–2:45 PM in Theater
Build Data Apps by Deploying ML Models as API Services
Ramesh Sampath
- Audience level:
- Novice
Description
As data scientists, we love building models using IPython Notebooks / Scikit-Learn / Pandas eco-system. But integrating these models with an web app can be a challenge. In this tutorial, we will take our machine learn ing models and make them available as APIs for use by Web and Mobile Apps. We will also build a simple webapp that uses our prediction service.
Abstract
Deploy your ML Models as a Service
In this talk, we will learn one way to take our Machine Learning models and make them available as a Prediction Service. We will work through the following steps.
- Create a Simple Machine learning Model using Scikit-Learn / Pandas
- Pickle the model
- Using Tornado Web App, Make this model available as an API Service
- Build an Web App that uses this deployed Model
- Add Authentication to our Prediction API
- Optionally, add Redis to Cache Prediction Results
- Deploy the model in the Cloud (AWS)
Please have Anaconda or Miniconda installed on your local machine. I will mostly be using Python 3.5, but Python 2.7 should be fine as well.
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