Introduction to Statistical and Machine Learning Methods for Data Science
1st Edition
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Additional Book Details
Boost your understanding of data science techniques to solve real-world problems <p><p>
Data science is an exciting, interdisciplinary field that extracts insights from data to solve business problems. This book introduces common data science techniques and methods and shows you how to apply them in real-world case studies. From data preparation and exploration to model assessment and deployment, this book describes every stage of the analytics life cycle, including a comprehensive overview of unsupervised and supervised machine learning techniques. The book guides you through the necessary steps to pick the best techniques and models and then implement those models to successfully address the original business need.<p>
No software is shown in the book, and mathematical details are kept to a minimum. This allows you to develop an understanding of the fundamentals of data science, no matter what background or experience level you have. <p> <p>
Additional resources for this book can be found by accessing the link below.
<p><p>
Book Review<p>
"A comprehensive and nifty book that takes the reader through the analytics lifecycle, discussing many data science methods, statistical approaches and machine learning techniques. The variety of case studies and tips along the way enhances your knowledge and capability, forming a practical understanding of data science". <p>Michelle Homes, Metacoda, Australia
| Sold By | SAS Institute |
|---|---|
| ISBNs | 9781953329646, 9781953329622, 9781953329608 |
| Publish Year | 2021 |
| Language | English |
| Number of Pages | 170 |
| Edition | 1st |
| Website | https://support.sas.com/pinheiro |