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Hands-On Machine Learning with Microsoft Excel 2019: Build complete data analysis flows, from data collection to visualization
87% of respondents would recommend this to a friend
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A practical guide to getting the most out of Excel, using it for data preparation, applying machine learning models (including cloud services) and understanding the outcome of the data analysis.
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What Stands Out
Product Details
| Publisher | Packt Publishing |
| Publication date | April 30, 2019 |
| Language | English |
| Print length | 254 pages |
| ISBN-10 | 1789345375 |
| ISBN-13 | 978-1789345377 |
| Item Weight | 15.5 ounces (439.43 grams) |
| Dimensions | 7.5 x 0.58 x 9.25 inches (19.1 x 1.5 x 23.5 cm) |
Who Should Buy?
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Beginners in Data Science
Individuals who are new to data analysis can easily learn concepts using familiar Excel tools without complex coding.
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Business Analysts
Professionals needing to quickly analyze and visualize data can leverage Excel for efficient reporting and insights.
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Educators and Students
Teachers and learners can use this resource to enhance their understanding of machine learning principles through hands-on practice.
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Advanced Data Scientists
Experienced analysts may find the Excel framework limiting for complex data analysis and advanced machine learning techniques.
Product Description
Hands-On Machine Learning with Microsoft Excel 2019: Build complete data analysis flows, from data collection to visualization
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Intelligence & Semantics Editorial Review
Hands-On Machine Learning with Microsoft Excel 2019: Build complete data analysis flows, from data collection to visualization is an excellent resource for beginners looking to dive into machine learning without the need for programming skills. This book, published by Packt Publishing, offers a detailed guide starting from the basics, moving through data cleansing, exploratory data analysis, and even integrating Azure ML with Excel for enhanced decision-making processes. Readers appreciate the practical examples and real-life problems provided, making the learning experience engaging and applicable. The structure and clarity of the content have earned it high praise, showcasing the book's effectiveness in teaching complex concepts in an accessible manner.
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Pros
- Clear explanations throughout the text
- Practical examples aid understanding
- Well-organized structure for learning
- Integration of Azure ML with Excel
- Ideal for non-programmers starting out
Cons
- Some readers may prefer more advanced topics
Product Price History
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Features & Benefits
- Use Excel for data preparation, machine learning models, and data analysis.
- Learn to import data from different data sources and perform preliminary data analysis.
- Understand correlations between variables and optimize input to machine learning models.
- Preview and cleanse datasets and evaluate different machine learning models using Excel.
- Learn basic concepts and how to calculate artificial neural networks.
- Connect Excel to Microsoft Azure cloud and build fully functional data analysis flows.
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