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Time Series Analysis
course content

Kursinnhold

Time Series Analysis

Time Series Analysis

1. Time Series: Let's Start
IntroductionPractical ExamplesModel TypesImplementation in PythonVisualization
2. Time Series Processing
Reading and Visualizing DataStationarityAutocorrelationDecomposition
3. Time Series Visualization
Simple Time SeriesCustomize Your PlotChallenge
4. Stationary Models
Examples of Stationary Time SeriesSimple Moving AverageAutoregressionAutoregressive-Integrated-Moving-Average ModelChallenge
5. Non-Stationary Models
Examples of Non-Stationary Time SeriesConvert Non-Stationary Data to StationaryChallenge 1Challenge 2
6. Solve Real Problems
Weather ForecastingStore Demand ForecastFinancial MarketsPredict the Emergence of Repeat CustomersMedicine: EEG Forecasting

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Challenge

Oppgave

Swipe to start coding

Create an autoregressive model to predict the dataset aapl.csv. After, print the results and the model error.

  1. Read the aapl.csv dataset.
  2. Create an autoregressive model (AutoReg) with 3 lags for the X data and assign it to the model variable.
  3. Fit model to the data and assign it to the model_fit variable.
  4. Predict the first 30 values.
  5. Visualize the results: display the first 30 values of X within the first call of the print() function, and first 30 values of the predictions within the second call.
  6. Calculate the RMSE (square root of the mean squared error) and display it.

Løsning

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Seksjon 4. Kapittel 5
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book
Challenge

Oppgave

Swipe to start coding

Create an autoregressive model to predict the dataset aapl.csv. After, print the results and the model error.

  1. Read the aapl.csv dataset.
  2. Create an autoregressive model (AutoReg) with 3 lags for the X data and assign it to the model variable.
  3. Fit model to the data and assign it to the model_fit variable.
  4. Predict the first 30 values.
  5. Visualize the results: display the first 30 values of X within the first call of the print() function, and first 30 values of the predictions within the second call.
  6. Calculate the RMSE (square root of the mean squared error) and display it.

Løsning

Switch to desktopBytt til skrivebordet for virkelighetspraksisFortsett der du er med et av alternativene nedenfor
Alt var klart?

Hvordan kan vi forbedre det?

Takk for tilbakemeldingene dine!

Seksjon 4. Kapittel 5
Switch to desktopBytt til skrivebordet for virkelighetspraksisFortsett der du er med et av alternativene nedenfor
Vi beklager at noe gikk galt. Hva skjedde?
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