{"page":"\n\n
\n
\n
\n
\n
\n\nVideo\n
\n

\nTrend Using Moving Average Filter\n

\n
\n
\nGet Free Access for 10 Days!\n
\n
\n
\n
\n
\n
×
\n\n\n
\n\nPublisher:\n\nPackt\n\n\n
\n
\nThis video extracts the trend using the moving average filter. This clip is from the chapter \"Data Processing for Timeseries Forecasting\" of the series \"A Practical Approach to Timeseries Forecasting Using Python\".This section focuses on...\nThis video extracts the trend using the moving average filter. This clip is from the chapter \"Data Processing for Timeseries Forecasting\" of the series \"A Practical Approach to Timeseries Forecasting Using Python\".This section focuses on data processing for timeseries forecasting.\n
\n
\n\n
\n
\n
\n
\n

Resource Details

\n
\n
\n
\n
Curator Rating
\n
\n
\n
\n
\n
\n
Educator Rating
Not yet Rated
\n
\n
\n
\n
\n
Grade
Higher Ed
\n
\n
\n
\n
\n
Subjects
Math
1 more...
\n
\n
\n
\n
\n
Media Type
Instructional Videos
\n
\n
\n
\n
\n
Source:
\n
\n
\n
\n
\n
\n
Date
\n
2023
\n
\n
\n
\n
\n\n\n
\n
\n
\n
\n
Audiences
For Teacher Use
2 more...
\n
\n
\n
\n
\n\n
\n
\n
\n
\n
\n

Concepts

\n
\n
linear regression, setting, series, plot, variables, length, values
\n
\n\n\n
\n
\n
\n
\n

Additional Tags

\n
\n
time series, time series forecasting, time series forecasting using python, python, univariate, multivariate, rnn, auto regression, arima, auto arima, sarima, sarimax, machine learning, lstm, stacked lstm, bilstm, stacked bilstm, pandas, numpy, matplotlib, scit learn, figure size, moving average, step size, write fit_x, write, copy, line, part, column, give, layout, paste, title, discuss, trend, make, discussed, command, change, plots, graph
\n
\n\n\n
\n
\n
\n
\n

Educator Ratings

\n
\n
\n
\n
\n
\n\nShow resource details\n
\n
\n\" data-title=\"Get Full Access\" data-container=\"body\" rel=\"popover\" tabindex=\"0\" aria-label=\"Play video: Trend Using Moving Average Filter\" href=\"/subscription/new\">\"Trend\n\n
\n
\n
\n
\n
\n\n"}