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Beginning Data Science in R: Data Analysis, Visualization, and Modelling for the Data Scientist 1st ed. Edition
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COP 336208
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Detalles de producto
| Publisher | Apress |
| Publication date | March 13, 2017 |
| Edition | 1st ed. |
| Language | English |
| Print length | 379 pages |
| ISBN-10 | 1484226704 |
| ISBN-13 | 978-1484226704 |
| Item Weight | 1.45 pounds (660 grams) |
| Dimensions | 7 x 0.79 x 10 inches (17.8 x 2 x 25.4 cm) |
Who Should Buy?
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Aspiring Data Scientists
Individuals looking to enter the data science field will find comprehensive resources for analysis and visualization in R.
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Students in Statistics
Students seeking practical applications of statistical methods can benefit from hands-on examples and exercises using R.
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Self-learners in R
Self-motivated learners aiming to master R programming for data analysis will appreciate the structured content and exercises.
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Advanced Data Professionals
Experienced data scientists may find the material too basic and lacking in advanced techniques and coverage.
DESCRIPCIÓN DEL PRODUCTO
Beginning Data Science in R: Data Analysis, Visualization, and Modelling for the Data Scientist 1st ed. Edition
About This Item
Introducing "Beginning Data Science in R: Data Analysis, Visualization, and Modelling for the Data Scientist 1st ed. Edition" Are you ready to unlock the power of data science in the world of e-commerce? Look no further than "Beginning Data Science in R: Data Analysis, Visualization, and Modelling for the Data Scientist 1st ed. Edition".
Whether you're an aspiring data scientist, an experienced analyst, or an e-commerce entrepreneur looking to gain valuable insights from your data, this book is your ultimate guide. It covers everything you need to know about harnessing the power of R programming language for effective data analysis, visualization, and modelling specifically tailored for the e-commerce industry. This comprehensive guide is packed with real-world examples and practical exercises that will help you master various data science techniques and apply them directly to your e-commerce business. From data cleaning and preprocessing to advanced data analysis, you'll learn how to manipulate, visualize, and explore your e-commerce data using R. But it doesn't stop there.
"Beginning Data Science in R" also delves into the world of machine learning, covering predictive modeling, data mining, and even neural networks specifically designed for e-commerce data analysis. You'll discover how to extract valuable insights from your data, optimize your e-commerce operations, and make data-driven decisions that drive business growth. This book also covers other essential topics such as time series analysis, text mining, data clustering, regression analysis, recommendation systems, and much more. With its step-by-step approach and easy-to-understand explanations, even beginners can quickly grasp complex data science concepts and start applying them to their e-commerce business. With "Beginning Data Science in R: Data Analysis, Visualization, and Modelling for the Data Scientist 1st ed.
Edition", you'll not only gain invaluable skills in e-commerce data analysis, but also learn best practices and industry-proven techniques that will set you apart from the competition. Get ready to transform your e-commerce business into a data-driven powerhouse. Don't miss out on this opportunity to take your e-commerce data analysis to the next level.
Order your copy today!.
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Data Mining Editorial Review
The Beginning Data Science in R book is a comprehensive guide for aspiring data scientists. It covers the essential concepts and techniques in data analysis, visualization, and modeling using the R programming language. The book provides clear explanations and examples, making it accessible for both beginners and experienced R users. The author's writing style is engaging and easy to understand. Moreover, the book includes various real-world datasets and practical exercises, allowing readers to apply their knowledge in a hands-on manner. Overall, this book is a valuable resource for anyone interested in learning data science and R.
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ventajas
- Comprehensive guide covering essential concepts and techniques in data science
- Clear explanations and examples
- Engaging and easy-to-understand writing style
- Includes real-world datasets and practical exercises
Contras
- Limited coverage of advanced topics in data science
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COP 336208
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