Verwandte Artikel zu Real-Time Demand Forecasting: Azure, ML, Demand Forecasting
- VerlagLAP LAMBERT Academic Publishing
- Erscheinungsdatum2020
- ISBN 10 6202674474
- ISBN 13 9786202674478
- EinbandTapa blanda
- SpracheEnglisch
- Anzahl der Seiten104
- Kontakt zum HerstellerNicht verfügbar
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Real-Time Demand Forecasting
Verlag:
LAP LAMBERT Academic Publishing, 2020
ISBN 10: 6202674474
ISBN 13: 9786202674478
Neu
Softcover
Anbieter: moluna, Greven, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Gupta PunitPunit Gupta is an Associate Professor in the Department of Computer and Communiction Engineering, Manipal University Jaipur, Jaipur, Rajisthan, India.Has got M.Tech. Degree in Computer Science and Engineering from Jaypee I. Bestandsnummer des Verkäufers 389068752
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Real-Time Demand Forecasting
Verlag:
LAP LAMBERT Academic Publishing Jul 2020, 2020
ISBN 10: 6202674474
ISBN 13: 9786202674478
Neu
Taschenbuch
Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The model which we have presented is a Linear Regression Model. In the results above we see that predictions can be done on the basis of the data available and is approximately accurate. An accurate forecast is very important for the demand planning team. The data used in this project and building the model is using the sales-in data for different stores. The important factor to be considered is the stability of the model and removing the game-playing. A community version of a platform is used to build the model. Linear Regression model is developed in pyspark. After the results are generated, dataframe of results is validated and generated and is sent backto the Azure SQL database to be used in Power BI.In the future work, different techniques will be considered and researched. Time-Series and Machine Learning to be built in one platform and check how the minimization of mse produces the forecast. The predictions can be hyper parameterized to give more accurately tuned results. Also, in the PowerBI report more measures and visualizations can be made on basis of individual's thought process. 104 pp. Englisch. Bestandsnummer des Verkäufers 9786202674478
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Real-Time Demand Forecasting
Verlag:
LAP LAMBERT Academic Publishing Jul 2020, 2020
ISBN 10: 6202674474
ISBN 13: 9786202674478
Neu
Taschenbuch
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. Neuware -The model which we have presented is a Linear Regression Model. In the results above we see that predictions can be done on the basis of the data available and is approximately accurate. An accurate forecast is very important for the demand planning team. The data used in this project and building the model is using the sales-in data for different stores. The important factor to be considered is the stability of the model and removing the game-playing. A community version of a platform is used to build the model. Linear Regression model is developed in pyspark. After the results are generated, dataframe of results is validated and generated and is sent backto the Azure SQL database to be used in Power BI.In the future work, different techniques will be considered and researched. Time-Series and Machine Learning to be built in one platform and check how the minimization of mse produces the forecast. The predictions can be hyper parameterized to give more accurately tuned results. Also, in the PowerBI report more measures and visualizations can be made on basis of individual¿s thought process.Books on Demand GmbH, Überseering 33, 22297 Hamburg 104 pp. Englisch. Bestandsnummer des Verkäufers 9786202674478
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Real-Time Demand Forecasting : Azure, ML, Demand Forecasting
Print-on-DemandAnbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The model which we have presented is a Linear Regression Model. In the results above we see that predictions can be done on the basis of the data available and is approximately accurate. An accurate forecast is very important for the demand planning team. The data used in this project and building the model is using the sales-in data for different stores. The important factor to be considered is the stability of the model and removing the game-playing. A community version of a platform is used to build the model. Linear Regression model is developed in pyspark. After the results are generated, dataframe of results is validated and generated and is sent backto the Azure SQL database to be used in Power BI.In the future work, different techniques will be considered and researched. Time-Series and Machine Learning to be built in one platform and check how the minimization of mse produces the forecast. The predictions can be hyper parameterized to give more accurately tuned results. Also, in the PowerBI report more measures and visualizations can be made on basis of individual's thought process. Bestandsnummer des Verkäufers 9786202674478
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