Deep Learning in R: A Data-Analytic Viewpoint
1
Installing Keras
2
Forecasting tomorrow’s market move: difficult binary classification
2.1
Purpose of analysis
2.2
Preparing our data objects
2.3
Fitting the model and monitoring performance
2.4
Running the fitted model on test data
3
To be continued
References
Published with bookdown
Deep Learning in R: A Data-Analytic Viewpoint
References
Baranowski, R., and P. Fryzlewicz. 2020.
“Multiscale Autoregression on Adaptively Detected Timescales.”
Preprint
.
http://stats.lse.ac.uk/fryzlewicz/amar/amar.pdf
.
Chollet, F., and J. J. Allare. 2018.
Deep Learning with
R
. Manning.