3.14 GB | 00:21:56 | mp4 | 1280X720 | 16:9
Genre:eLearning |Language:English
Files Included :
001 Course Introduction (78.16 MB)
003 Course Material (43.64 MB)
001 Game Plan (17.62 MB)
002 Why Forecasting (15.4 MB)
003 Time Series Data and Case Study Briefing (18.52 MB)
004 Python - Set Working Directory (17.1 MB)
005 Python - Importing Libraries (5.1 MB)
006 Python - Loading Data (26.67 MB)
007 Python - Forming Data Set (50.69 MB)
008 Python - Renaming Dependent Variable (13.53 MB)
009 Python - Index Frequency (14.4 MB)
010 Python - Visualization (19.79 MB)
001 Game Plan (22.87 MB)
002 Seasonal Decomposition (17.97 MB)
003 Prepare Script (28.67 MB)
004 Multiplicative and Additive seasonality (15.55 MB)
005 Python - Seasonal Decomposition (45.47 MB)
006 Error Modelling and Stock Data (15.54 MB)
007 Python - Seasonality graphs (24.13 MB)
001 Game Plan (15.91 MB)
002 Training and Test Set (7.87 MB)
003 Python - Prepare Script (20.48 MB)
004 Python - Training and Test Set (20.85 MB)
005 Exponential Smoothing and Holt-Winters (12.56 MB)
006 Python - Holt-Winters (26.51 MB)
007 Python - Predictions (14.74 MB)
008 Python - Visualization (21.62 MB)
009 Assessing Time Series Models (16.13 MB)
010 Python - MAE and RSME (23.78 MB)
011 Python - MAPE function (17.79 MB)
012 Python - Exporting Forecasts (15.66 MB)
013 Python - Preparing Master Script (34.47 MB)
014 Pros, Cons and Challenge (41.41 MB)
015 Python - Challenge Solutions (61.79 MB)
001 Game Plan (19.28 MB)
002 TBATS introduction (6.1 MB)
003 Python - Prepare Script and Install Package (22.07 MB)
004 Autoregressive and Moving Average components (12.49 MB)
005 Trigonometric Seasonality and Box Cox (10.99 MB)
006 Python - TBATS model (19.13 MB)
007 Python - Predictions and Plotting (24.92 MB)
008 Python - Accuracy Assessment and Exporting (15.71 MB)
009 Pros, Cons and Challenge (37.57 MB)
010 Python - Challenge Solutions (62.47 MB)
001 Game Plan (14.19 MB)
002 ARIMA and ARMA recap (9.68 MB)
003 Python - Prepare Script (18.72 MB)
004 Stationarity (17.94 MB)
005 Python - Augmented Dickey Fuller Test (17.61 MB)
006 Exogenous Variables (10.47 MB)
007 Python - Isolating Regressors (14.32 MB)
008 Optimizing factors in ARIMA and SARIMA (12.29 MB)
009 AIC and BIC (8.84 MB)
010 Python - SARIMAX model (34.71 MB)
011 Python - Model Summary and Predictions (29.39 MB)
012 Python - Visualization, Assessment and Exporting (25.02 MB)
013 Pros, Cons and Challenge (25.95 MB)
014 Python - Challenge Solutions (106.31 MB)
001 Game Plan (12.59 MB)
002 Structural Time Series (6.07 MB)
003 Python - Prepare Script (19.39 MB)
004 TensorFlow Structural Time Series (4.01 MB)
005 Python - Regressors (32.12 MB)
006 Python - Isolate Dependent Variable (8.8 MB)
007 Python - Weekly Seasonality (27.43 MB)
008 Python - Monthly Seasonality (29.11 MB)
009 Python - Trend and Autoregressive Terms (20.07 MB)
010 Python - TensorFlow Model (28.62 MB)
011 Monte Carlo and Bayes Theorem (14.69 MB)
012 Python - Fitting Model (30.23 MB)
013 Python - Forecasting (21.17 MB)
014 Python - Formatting Predictions (21.14 MB)
015 Python - Visualization, Assessment and Exporting (21.09 MB)
016 Pros, Cons and Challenge (27.69 MB)
017 Python - Challenge Solutions (142.88 MB)
001 Game Plan (21.4 MB)
002 Facebook Prophet Introduction (15.23 MB)
003 Python - Importing Libraries and Data (23.26 MB)
004 Python - Transforming Date Variable (12.2 MB)
005 Python - Renaming Variables (13.96 MB)
006 Dynamic Holidays (6.1 MB)
007 Python - holidays (28.55 MB)
008 Python - Removing Variable and Training Set (12.83 MB)
009 Facebook Prophet Components (5.79 MB)
010 Python - Prophet model (55.99 MB)
011 Python - Future Dataframe (32.3 MB)
012 Python - Forecasting (26.08 MB)
013 Python - Visualization (31.93 MB)
014 Python - Model Assessment (12.53 MB)
015 Cross-Validation (3.26 MB)
016 Python - Cross-Validation (15.95 MB)
017 Python - Cross-Validation results (35.46 MB)
018 Parameters to be tuned (2.8 MB)
019 Python - Parameter Grid (28.74 MB)
020 Python - Hyperparameter Tuning (75.34 MB)
021 Python - Getting Best Parameters (17.6 MB)
022 Python - Final Prophet Model (58.61 MB)
023 Pros, Cons and Challenge (57.66 MB)
024 Python - Challenge Solutions (116.38 MB)
001 Game Plan (13.77 MB)
002 Prophet + XGBoost step by step (4.27 MB)
003 Python - Prepare Script (50.25 MB)
004 XGBoost (25.73 MB)
005 Python - Extracting Prophet Variables (45.16 MB)
006 Python - Training and Test Set (12.72 MB)
007 Python - Isolate X and Y (14.39 MB)
008 XGBoost Matrices (11.51 MB)
009 XGBoost Quirks and Parameters (12.27 MB)
010 Python - Setting Parameters (18.89 MB)
011 Python - XGBoost Model (30.54 MB)
012 Python - Forecasting (17.14 MB)
013 Python - Visualization (21.6 MB)
014 Python - Assessment and Export (15.23 MB)
015 Pros, Cons and Challenge (43.16 MB)
016 Python - Challenge Solutions (105.66 MB)
001 Game Plan (17.25 MB)
002 Why Ensemble (14.33 MB)
003 Python - Prepare Script (38.23 MB)
004 Python - Loading Predictions (44.63 MB)
005 Python - Ensemble Forecast (18.25 MB)
006 Python - Visualization and Assessment (41 MB)
007 Pros and Cons (4.32 MB)
003 Course Material (43.64 MB)
001 Game Plan (17.62 MB)
002 Why Forecasting (15.4 MB)
003 Time Series Data and Case Study Briefing (18.52 MB)
004 Python - Set Working Directory (17.1 MB)
005 Python - Importing Libraries (5.1 MB)
006 Python - Loading Data (26.67 MB)
007 Python - Forming Data Set (50.69 MB)
008 Python - Renaming Dependent Variable (13.53 MB)
009 Python - Index Frequency (14.4 MB)
010 Python - Visualization (19.79 MB)
001 Game Plan (22.87 MB)
002 Seasonal Decomposition (17.97 MB)
003 Prepare Script (28.67 MB)
004 Multiplicative and Additive seasonality (15.55 MB)
005 Python - Seasonal Decomposition (45.47 MB)
006 Error Modelling and Stock Data (15.54 MB)
007 Python - Seasonality graphs (24.13 MB)
001 Game Plan (15.91 MB)
002 Training and Test Set (7.87 MB)
003 Python - Prepare Script (20.48 MB)
004 Python - Training and Test Set (20.85 MB)
005 Exponential Smoothing and Holt-Winters (12.56 MB)
006 Python - Holt-Winters (26.51 MB)
007 Python - Predictions (14.74 MB)
008 Python - Visualization (21.62 MB)
009 Assessing Time Series Models (16.13 MB)
010 Python - MAE and RSME (23.78 MB)
011 Python - MAPE function (17.79 MB)
012 Python - Exporting Forecasts (15.66 MB)
013 Python - Preparing Master Script (34.47 MB)
014 Pros, Cons and Challenge (41.41 MB)
015 Python - Challenge Solutions (61.79 MB)
001 Game Plan (19.28 MB)
002 TBATS introduction (6.1 MB)
003 Python - Prepare Script and Install Package (22.07 MB)
004 Autoregressive and Moving Average components (12.49 MB)
005 Trigonometric Seasonality and Box Cox (10.99 MB)
006 Python - TBATS model (19.13 MB)
007 Python - Predictions and Plotting (24.92 MB)
008 Python - Accuracy Assessment and Exporting (15.71 MB)
009 Pros, Cons and Challenge (37.57 MB)
010 Python - Challenge Solutions (62.47 MB)
001 Game Plan (14.19 MB)
002 ARIMA and ARMA recap (9.68 MB)
003 Python - Prepare Script (18.72 MB)
004 Stationarity (17.94 MB)
005 Python - Augmented Dickey Fuller Test (17.61 MB)
006 Exogenous Variables (10.47 MB)
007 Python - Isolating Regressors (14.32 MB)
008 Optimizing factors in ARIMA and SARIMA (12.29 MB)
009 AIC and BIC (8.84 MB)
010 Python - SARIMAX model (34.71 MB)
011 Python - Model Summary and Predictions (29.39 MB)
012 Python - Visualization, Assessment and Exporting (25.02 MB)
013 Pros, Cons and Challenge (25.95 MB)
014 Python - Challenge Solutions (106.31 MB)
001 Game Plan (12.59 MB)
002 Structural Time Series (6.07 MB)
003 Python - Prepare Script (19.39 MB)
004 TensorFlow Structural Time Series (4.01 MB)
005 Python - Regressors (32.12 MB)
006 Python - Isolate Dependent Variable (8.8 MB)
007 Python - Weekly Seasonality (27.43 MB)
008 Python - Monthly Seasonality (29.11 MB)
009 Python - Trend and Autoregressive Terms (20.07 MB)
010 Python - TensorFlow Model (28.62 MB)
011 Monte Carlo and Bayes Theorem (14.69 MB)
012 Python - Fitting Model (30.23 MB)
013 Python - Forecasting (21.17 MB)
014 Python - Formatting Predictions (21.14 MB)
015 Python - Visualization, Assessment and Exporting (21.09 MB)
016 Pros, Cons and Challenge (27.69 MB)
017 Python - Challenge Solutions (142.88 MB)
001 Game Plan (21.4 MB)
002 Facebook Prophet Introduction (15.23 MB)
003 Python - Importing Libraries and Data (23.26 MB)
004 Python - Transforming Date Variable (12.2 MB)
005 Python - Renaming Variables (13.96 MB)
006 Dynamic Holidays (6.1 MB)
007 Python - holidays (28.55 MB)
008 Python - Removing Variable and Training Set (12.83 MB)
009 Facebook Prophet Components (5.79 MB)
010 Python - Prophet model (55.99 MB)
011 Python - Future Dataframe (32.3 MB)
012 Python - Forecasting (26.08 MB)
013 Python - Visualization (31.93 MB)
014 Python - Model Assessment (12.53 MB)
015 Cross-Validation (3.26 MB)
016 Python - Cross-Validation (15.95 MB)
017 Python - Cross-Validation results (35.46 MB)
018 Parameters to be tuned (2.8 MB)
019 Python - Parameter Grid (28.74 MB)
020 Python - Hyperparameter Tuning (75.34 MB)
021 Python - Getting Best Parameters (17.6 MB)
022 Python - Final Prophet Model (58.61 MB)
023 Pros, Cons and Challenge (57.66 MB)
024 Python - Challenge Solutions (116.38 MB)
001 Game Plan (13.77 MB)
002 Prophet + XGBoost step by step (4.27 MB)
003 Python - Prepare Script (50.25 MB)
004 XGBoost (25.73 MB)
005 Python - Extracting Prophet Variables (45.16 MB)
006 Python - Training and Test Set (12.72 MB)
007 Python - Isolate X and Y (14.39 MB)
008 XGBoost Matrices (11.51 MB)
009 XGBoost Quirks and Parameters (12.27 MB)
010 Python - Setting Parameters (18.89 MB)
011 Python - XGBoost Model (30.54 MB)
012 Python - Forecasting (17.14 MB)
013 Python - Visualization (21.6 MB)
014 Python - Assessment and Export (15.23 MB)
015 Pros, Cons and Challenge (43.16 MB)
016 Python - Challenge Solutions (105.66 MB)
001 Game Plan (17.25 MB)
002 Why Ensemble (14.33 MB)
003 Python - Prepare Script (38.23 MB)
004 Python - Loading Predictions (44.63 MB)
005 Python - Ensemble Forecast (18.25 MB)
006 Python - Visualization and Assessment (41 MB)
007 Pros and Cons (4.32 MB)
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