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- 389pages
- 14 heures de lecture
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Use business intelligence to power corporate growth, increase efficiency, and improve corporate decision making. With this practical book featuring hands-on examples in Power BI with basic Python and R code, you'll explore the most relevant AI use cases for BI, including improved forecasting, automated classification, and AI-powered recommendations. And you'll learn how to draw insights from unstructured data sources like text, document, images files. Author Tobias Zwingmann helps BI professionals, business analysts, and data analytics understand high-impact areas of artificial intelligence. You'll learn how to leverage popular AI-as-a-service and AutoML platforms to ship enterprise-grade proofs of concept without the help of software engineers or data scientists.
Achat du livre
AI-Powered Business Intelligence, Tobias Zwingmann
- Langue
- Année de publication
- 2022
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- (souple)
Modes de paiement
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- Titre
- AI-Powered Business Intelligence
- Sous-titre
- Improving Forecasts and Decision Making with Machine Learning
- Langue
- Anglais
- Auteurs
- Tobias Zwingmann
- Éditeur
- O'Reilly Media
- Publié
- 2022
- Format
- souple
- Pages
- 389
- ISBN10
- 1098111478
- ISBN13
- 9781098111472
- Séries
- Mots clés
- Commerce, Informatique & Internet, Économie, Intelligence Artificielle, Traitement des données, Apprentissage automatique
- Description
- Use business intelligence to power corporate growth, increase efficiency, and improve corporate decision making. With this practical book featuring hands-on examples in Power BI with basic Python and R code, you'll explore the most relevant AI use cases for BI, including improved forecasting, automated classification, and AI-powered recommendations. And you'll learn how to draw insights from unstructured data sources like text, document, images files. Author Tobias Zwingmann helps BI professionals, business analysts, and data analytics understand high-impact areas of artificial intelligence. You'll learn how to leverage popular AI-as-a-service and AutoML platforms to ship enterprise-grade proofs of concept without the help of software engineers or data scientists.