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_12

12. Case Study Part 3: Enriching Content with Fundamental Financial Information

Manuel Amunategui¹  and Mehdi Roopaei²

(1)

Portland, Oregon, USA

(2)

Platteville, Wisconsin, USA

 

Predicting the stock market with fundamental financial data aggregation on PythonAnywhere.

We’re going to keep adding features to our “ Pair Trading Booth ” web application (Figure 12-1).

Figure 12-1

The final web application for this chapter

So far, we told our visitors about the best pair trade to make, showed them the related financial ...