Background in politics, commodity trading, and converted to being a data engineer in 2017. I worked with Django, Flask, Plotly, and Vue.JS, but now Airflow and PySpark for ETL pipelines.
There is something called the M-competitions where different techniques are used for times series forecasting and compared (en.wikipedia.org/wiki/Makridakis_C...). Traditional statistical models regularly outperform the Deep Thinking models.
not yet, who knows in the future with more data looking at more indicators, would you show me some way? I appreciate the idea, thank you :)
There are lots of examples with things like ARIMA. Give it a try! machinelearningmastery.com/arima-f...
There is something called the M-competitions where different techniques are used for times series forecasting and compared (en.wikipedia.org/wiki/Makridakis_C...). Traditional statistical models regularly outperform the Deep Thinking models.
Wow, very good, thank you very much for sharing; I will start studying this option; I do not promise anything for this year. =)