Click on each picture to find out about it on X. Box-Jenkins methodologyARIMA modelsTime Series models classificationMissing data is a problemHandle Missing ValuesTest for Granger causality2D graphsSMOTE for imbalanced dataGranger causalitySteps in DS projectFeature selectionClean your time series dataExample of nature of missing dataImbalanced dataForecast BiasPrediction Direction AccuracyArchitecture of RNNsNature of missing dataBest scenarios for ProphetMinMax ScalingTriple Exponential SmoothingTime Series with XGBoostSources of Missing dataForecast Interval Coverage as a Performance MetricTime biasAdvantages of ProphetFeature scalingRecurrent Neural NetworksIntroduction to RNNsSimple Exponential SmoothingSelect your Time Series modelWhen not to use Prophet?How to address imbalanced data?Model doesn't behave well with real dataReframe Time Series data into Supervised Learning Double Exponential SmoothingAdvantages of RNNsWhy should you split your datasetWhat kind of Time Series model is Prophet? . . . . . . . . . . . . . . . . Follow me on X