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What kind of Time Series model is Prophet?
What kind of Time Series model is Prophet?
Advantages of RNNs
Advantages of RNNs
2D graphs
2D graphs
Test for Granger causality
Test for Granger causality
Recurrent Neural Networks
Recurrent Neural Networks
Steps in DS project
Steps in DS project
Time Series models classification
Time Series models classification
Handle Missing Values
Handle Missing Values
Missing data is a problem
Missing data is a problem
Time Series with XGBoost
Time Series with XGBoost
Prediction Direction Accuracy
Prediction Direction Accuracy
Example of nature of missing data
Example of nature of missing data
Imbalanced data
Imbalanced data
Architecture of RNNs
Architecture of RNNs
Reframe Time Series data into Supervised Learning
Reframe Time Series data into Supervised Learning
SMOTE for imbalanced data
SMOTE for imbalanced data
Box-Jenkins methodology
Box-Jenkins methodology
Advantages of Prophet
Advantages of Prophet
Feature scaling
Feature scaling
Granger causality
Granger causality
Clean your time series data
Clean your time series data
Best scenarios for Prophet
Best scenarios for Prophet
ARIMA models
ARIMA models
Time bias
Time bias
Why should you split your dataset
Why should you split your dataset
Select your Time Series model
Select your Time Series model
Forecast Interval Coverage as a Performance Metric
Forecast Interval Coverage as a Performance Metric
Double Exponential Smoothing
Double Exponential Smoothing
Feature selection
Feature selection
Simple Exponential Smoothing
Simple Exponential Smoothing
Nature of missing data
Nature of missing data
Sources of Missing data
Sources of Missing data
When not to use Prophet?
When not to use Prophet?
How to address imbalanced data?
How to address imbalanced data?
Forecast Bias
Forecast Bias
Model doesn't behave well with real data
Model doesn't behave well with real data
Triple Exponential Smoothing
Triple Exponential Smoothing
MinMax Scaling
MinMax Scaling
Introduction to RNNs
Introduction to RNNs

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