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1
Hands-on Time Series Analysis with Python: From Basics to Bleeding Edge Techniques
Apress
B V Vishwas
,
Ashish Patel
y_true
y_pred
import
figure
function
horizon
values
forecast
pandas
predicted
trend
dataset
stationary
actual
smoothing
neural
np.array
lstm
exponential
activation
validation
epochs
traffic_volume
weights
differencing
step
range
plt.plot
rmse
univariate
val_loss
metrics.mean_squared_error
define
seasonal
timeseries_evaluation_metrics_func
previous
summary
validate
shows
forecasting
seasonality
val_rescaled
mean_absolute_percentage_error
check
gradient
network
plt.show
arima
columns
predicted_results
Anno:
2020
Lingua:
english
File:
EPUB, 23.35 MB
I tuoi tag:
0
/
0
english, 2020
2
Hands-on Time Series Analysis With Python: From Basics To Bleeding Edge Techniques
Apress
B. V. Vishwas
,
Ashish Patel
import
techniques
y_true
y_pred
figure
function
bleeding
edge
horizon
values
univariate
pandas
forecast
predicted
smoothing
trend
stationary
dataset
regression
plt.plot
multivariate
actual
summary
lstm
neural
np.array
exponential
activation
differencing
validate
validation
epochs
weights
step
range
preparation
rmse
traffic_volume
val_loss
metrics.mean_squared_error
define
seasonal
methods
prophet
timeseries_evaluation_metrics_func
previous
forecasting
seasonality
shows
val_rescaled
Anno:
2020
Lingua:
english
File:
PDF, 17.03 MB
I tuoi tag:
0
/
5.0
english, 2020
3
Hands-on Time Series Analysis with Python: From Basics to Bleeding Edge Techniques
Apress
B. V. Vishwas
,
Ashish Patel
y_true
y_pred
import
figure
function
horizon
values
forecast
pandas
predicted
trend
dataset
stationary
actual
smoothing
neural
np.array
lstm
exponential
activation
validation
epochs
traffic_volume
weights
differencing
step
range
plt.plot
rmse
univariate
val_loss
metrics.mean_squared_error
define
seasonal
timeseries_evaluation_metrics_func
previous
summary
validate
shows
forecasting
seasonality
val_rescaled
mean_absolute_percentage_error
check
gradient
network
plt.show
arima
columns
predicted_results
Anno:
2020
Lingua:
english
File:
EPUB, 23.35 MB
I tuoi tag:
0
/
0
english, 2020
1
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