Created on 11-25-2019 11:41 AM - edited on 09-02-2020 03:55 PM by cjervis
New in Cloudera Machine Learning (CML) 1.2 we’re excited to announce support for hosting persistent web based applications and dashboards using frameworks like Flask, Dash and Shiny to share analytics results and insights with business stakeholders.
Example Use case
Here’s a quick example of how it works based on a use-case involving New York City transportation data:
This example uses the most recent data from Citibike and NYC TLC for-hire vehicle (FHV) data.
Publishing the app
Two pre-trained machine learning models (simple sklearn logistic regression models) are served by CML to be accessed by the application via API. As our focus is mainly on hosting the application using CML, let’s jump straight to that. Here’s a step-by-step instruction on how to leverage the “app hosting” capability of CML.
Monte Carlo Simulation Results
This visualisation shows New York City segmented into taxi zones. For each zone the colour chart shows which transport mode is faster from a selected reference zone coloured red. The user can either click on each zone to explore new relationships or press SPACEBAR to run an animated loop for the selected zone, cycling through all time bins.
Outlier Prediction Model
The user can press T to launch this animation. Trips between Trader Joe store locations are replayed and models served via CML are queried which classify each trip as an outlier or not. Outliers are visualised using red tracks, while normal trips are visualised in blue (Citibike) and yellow (FHV)
This was a simple demonstration of CML’s new Analytical Applications feature. For at step-by-step how-to including building the application, see Building an Interactive Machine Learning Application with CML. You can also tune-in for our weekly webinar series with technical experts to learn more about Cloudera's machine learning platform for enterprise data science teams. Each session will feature a product overview including a live demo and Q&A for both end-user, data scientists and administrators. For the webinar series in North America, click here. For the webinar series in Europe, Middle East and Africa, click here.