Paramètres
- 254pages
- 9 heures de lecture
En savoir plus sur le livre
This practical guide helps users maximize Excel for data preparation, machine learning model application, and data analysis interpretation. As advancements in technology evolve, many Excel users may feel overshadowed by these innovations. However, a significant portion of machine learning model development can be accomplished within Excel. The book begins with a clear introduction to machine learning concepts, ensuring accessibility for all readers. It outlines each phase of a machine learning project, including data collection, integration from various sources, model development, and result visualization using Excel’s features. Each chapter includes examples and hands-on exercises that demonstrate how to effectively combine Excel functions, add-ins, and connections to databases and cloud services for comprehensive data analysis. Various machine learning models are presented, tailored to different data types. The book concludes with advanced use cases involving Automated Machine Learning and artificial neural networks, showcasing the future of analysis. This resource is ideal for data analysis and machine learning enthusiasts, project managers, and those seeking to perform essential machine learning tasks with minimal coding. A working knowledge of Excel is necessary to fully benefit from the content.
Achat du livre
Hands-On Machine Learning with Microsoft Excel 2019, Julio Cesar Rodriguez Martino
- Langue
- Année de publication
- 2019
- Reliure
- (souple),
- État du livre
- Très bon
- Prix
- 14,49 €
Modes de paiement
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- Titre
- Hands-On Machine Learning with Microsoft Excel 2019
- Sous-titre
- Build Complete Data Analysis Flows, from Data Collection to Visualization
- Langue
- Anglais
- Éditeur
- Packt Publishing
- Publié
- 2019
- Format
- souple
- Pages
- 254
- ISBN10
- 1789345375
- ISBN13
- 9781789345377
- Séries
- Mots clés
- Nonfiction, Technologie & Ingénierie, Informatique & Internet, Intelligence Artificielle, Base de données, Apprentissage automatique
- Description
- This practical guide helps users maximize Excel for data preparation, machine learning model application, and data analysis interpretation. As advancements in technology evolve, many Excel users may feel overshadowed by these innovations. However, a significant portion of machine learning model development can be accomplished within Excel. The book begins with a clear introduction to machine learning concepts, ensuring accessibility for all readers. It outlines each phase of a machine learning project, including data collection, integration from various sources, model development, and result visualization using Excel’s features. Each chapter includes examples and hands-on exercises that demonstrate how to effectively combine Excel functions, add-ins, and connections to databases and cloud services for comprehensive data analysis. Various machine learning models are presented, tailored to different data types. The book concludes with advanced use cases involving Automated Machine Learning and artificial neural networks, showcasing the future of analysis. This resource is ideal for data analysis and machine learning enthusiasts, project managers, and those seeking to perform essential machine learning tasks with minimal coding. A working knowledge of Excel is necessary to fully benefit from the content.