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Course Introduction
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Course Material
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Why Forecasting Matters
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Game Plan
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TIme Series Data
Урок 6. 00:01:44
Case Study Briefing
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Python - Directory and Libraries
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Python - Loading the Data
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Python - Renaming Variable
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Python - Summary Statistics
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Additive vs. Multiplicative Seasonality
Урок 12. 00:08:19
Python - Seasonal Decomposition
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Python - Seasonal Graphs
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Python - Visualization - Basic Plot
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Python - Visualization - Customization
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Python - Visualization -Adding Events
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Python - Correlation
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Auto-Correlation Plots
Урок 19. 00:03:21
Python - Auto-Correlation Plot
Урок 20. 00:02:31
Python - Useful Commands Template
Урок 21. 00:01:37
Facebook Prophet Game Plan
Урок 22. 00:04:43
Structural Time Series and Facebook Prophet
Урок 23. 00:03:51
Python - Preparing the Script
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Python - Date Variable
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Python - Easter
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Python - Thanksgiving
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Python - Wrapping Up the Events
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Facebook Prophet Parameters
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Facebook Prophet Model
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Cross-Validation
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Python - Cross-Validation
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Assessing Model Errors
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Python - Cross-Validation Performance and Plot
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Parameter Tuning
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Python - Parameter Grid
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Python - Parameter Tuning
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Python - Best Parameters and Exporting
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Python - Building Script
Урок 39. 00:05:55
Python - Preparing Data Sets
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Python - Final Facebook Prophet Model
Урок 41. 00:07:37
Python - Forecasting
Урок 42. 00:05:16
Python - Exporting Forecast
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Facebook Prophet Pros and Cons
Урок 44. 00:01:53
SARIMAX Game Plan
Урок 45. 00:03:06
ARIMA
Урок 46. 00:03:30
Python - Preparing Script
Урок 47. 00:01:55
Auto-Regressive
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Integrated
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Python - Stationarity and Differencing
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Moving Average Component
Урок 51. 00:03:16
Optimization Factors
Урок 52. 00:05:12
Python - SARIMAX Model
Урок 53. 00:08:19
Python - Cross-Validation
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Python - Parameter Grid
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Python - Parameter Tuning
Урок 56. 00:04:27
Python - Exporting Best Parameters
Урок 57. 00:03:28
Python - Preparing the Script
Урок 58. 00:02:57
Python - Preparing Data
Урок 59. 00:04:03
Python - Tuned SARIMAX Model
Урок 60. 00:04:29
Python - Forecasting
Урок 61. 00:03:55
Python - Visualization and Export
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SARIMAX Pros and Cons
Урок 63. 00:01:36
LinkedIn Silverkite Game Plan
Урок 64. 00:03:09
LinkedIn Silverkite
Урок 65. 00:03:12
Silverkite vs. Prophet
Урок 66. 00:10:06
Python - Libraries and Data
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Python - Preparing Data
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Python - Metadata
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Silverkite Components
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Growth Terms
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Python - Growth Terms
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Seasonality Terms
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Python - Seasonality
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Python - Available Countries and Holidays
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Python - Holidays
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Python - Changepoints
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Python - Regressors
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Lagged Regressors
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Python - Lagged Regressors
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Python - Autoregression
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Fitting Algorithms Possibilities
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Ridge Regression
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XGBoost
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Boosting
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Feature Sampling
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Python - Custom Fit Algorithm
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Python - Silverkite Model
Урок 88. 00:08:28
Python - Cross-Validation Configuration
Урок 89. 00:06:02
Python - SIlverkite Parameter Tuning
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Python - Visualization and Preparing Results
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Python - Exporting Best Parameters
Урок 92. 00:03:34
Python - Preparing Script
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Python - Best Parameters and Silverkite Model
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Python - Summary and Visualization
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Python - Exporting Forecasts
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Pros and Cons
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Recurrent Neural Networks (RNN) Long Short-Term Memory (LSTM) Game Plan
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Simple Neural Network
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Recurrent Neural Networks (RNN)
Урок 100. 00:05:32
Long Short-Term Memory (LSTM)
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Python - Libraries and Data
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Python - Time Series Objects
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Python - Time Variables
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Python - Scaling Variables
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LSTM Parameters
Урок 106. 00:08:58
Python - LSTM Model
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Python - Cross-Validation
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Python - CV Performance
Урок 109. 00:04:22
Python - Parameter Grid
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Python - Parameter Tuning (Round 1)
Урок 111. 00:06:43
Python - Parameter Tuning (Round 2)
Урок 112. 00:02:29
Python - Parameter Tuning (Final Results)
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Python - Preparing Script
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Python - Preparing Inputs
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Python - Tuned LSTM Model
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Python - Predictions and Exporting
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LSTM Pros and Cons
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Ensemble Game Plan
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Ensemble Mechanism
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Python - Preparing Script and Loading Predictions
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Python - Loading Errors
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Python - Forecasting Weights
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Python - Ensemble Forecast and Visualization
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Ensemble Pros and Cons
