Monetizing Machine Learning: Quickly Turn Python ML Ideas into Web Applications on the Serverless Cloud

© Manuel Amunategui, Mehdi Roopaei 2018

Manuel Amunategui and Mehdi RoopaeiMonetizing Machine Learninghttps://doi.org/10.1007/978-1-4842-3873-8_5

5. Case Study Part 1: Supporting Both Web and Mobile Browsers

Manuel Amunategui¹  and Mehdi Roopaei²

(1)

Portland, Oregon, USA

(2)

Platteville, Wisconsin, USA

 

Predicting the stock market with web and mobile platforms support on PythonAnywhere.com.

For the first part of our case study, we are going to create a simple trade alerting system. The tool will scan a number of stocks and alert the viewer of any interesting trade setups. The design will be kept simple to work well on both regular and mobile web pages (Figure 5-1).

Figure 5-1

The final web application for this chapter

Machine learning and quantitative trading ...