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## ----setup, include=FALSE-----------------------------------------------------
knitr::opts_chunk$set(echo = TRUE,eval = FALSE,echo = T)
## -----------------------------------------------------------------------------
# reticulate::py_install('git+https://github.com/tcapelle/timeseries_fastai.git', pip = TRUE)
## -----------------------------------------------------------------------------
#
# library(dplyr)
# library(fastai)
#
# df = data.table::fread('https://raw.githubusercontent.com/facebook/prophet/master/examples/example_wp_log_peyton_manning.csv')
## -----------------------------------------------------------------------------
# split_idx = which(df$ds=='2016-01-01') # take 1 year for validation
#
# y = df$y
#
# df = timetk::tk_augment_timeseries_signature(df) %>%
# mutate_if(is.factor, as.numeric) %>%
# select(-ds, -hour, -minute, -second, -hour12, -am.pm, -y) %>%
# scale() %>% data.table::as.data.table()
#
# df[is.na(df)]=0
# df$y = y
## -----------------------------------------------------------------------------
# df_train = df[1:split_idx,]
# df_test = df[(split_idx+1):nrow(df),]
#
# x_cols = setdiff(colnames(df_train),'y')
## -----------------------------------------------------------------------------
# dls = TSDataLoaders_from_dfs(df_train, df_test, x_cols = x_cols, label_col = 'y', bs=60,
# y_block = RegressionBlock())
#
# dls %>% show_batch()
#
# inception = create_inception(1, 1)
#
# learn = Learner(dls, inception, metrics=list(mae(), rmse()))
## -----------------------------------------------------------------------------
# lrs = learn %>% lr_find()
#
# learn %>% plot_lr_find()
## -----------------------------------------------------------------------------
# learn %>% fit_one_cycle(30, 1e-5, cbs = EarlyStoppingCallback(patience = 5))
#
# learn %>% predict(df_test)
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