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Data Science and Machine Learning for Non Programmers Using SAS Enterprise Miner 1st Edition by Dothang Truong ISBN 0367755386 9780367755386

Name: Data Science and Machine Learning for Non Programmers Using SAS Enterprise Miner 1st Edition by Dothang Truong ISBN 0367755386 9780367755386
SKU: EB-54764720
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Data Science and Machine Learning for Non-Programmers: Using SAS Enterprise Miner 1st Edition Dothang Truong Digital Instant Download

Author(s): Dothang Truong

Edition: 1

File Details: PDF, 35.86 MB

Year: 2024

Language: English

SKU: EB-54764720 Category: Uncategorized Tag: Dothang Truong

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Data Science and Machine Learning for Non Programmers Using SAS Enterprise Miner 1st Edition by Dothang Truong – Ebook PDF Instant Download/Delivery: 0367755386 ,9780367755386
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ISBN 10: 0367755386
ISBN 13: 9780367755386
Author: Dothang Truong

As data continues to grow exponentially, knowledge of data science and machine learning has become more crucial than ever. Machine learning has grown exponentially; however, the abundance of resources can be overwhelming, making it challenging for new learners. This book aims to address this disparity and cater to learners from various non-technical fields, enabling them to utilize machine learning effectively. Adopting a hands-on approach, readers are guided through practical implementations using real datasets and SAS Enterprise Miner, a user-friendly data mining software that requires no programming. Throughout the chapters, two large datasets are used consistently, allowing readers to practice all stages of the data mining process within a cohesive project framework. This book also provides specific guidelines and examples on presenting data mining results and reports, enhancing effective communication with stakeholders. Designed as a guiding companion for both beginners and experienced practitioners, this book targets a wide audience, including students, lecturers, researchers, and industry professionals from various backgrounds.

Data Science and Machine Learning for Non Programmers Using SAS Enterprise Miner 1st Edition Table of contents:

Part I Introduction to Data Mining

1. Introduction to Data Mining and Data Science

2. Data Mining Processes, Methods, and Software

3. Data Sampling and Partitioning

4. Data Visualization and Exploration

5. Data Modification

Part II Data Mining Methods

6. Model Evaluation

7. Regression Methods

8. Decision Trees

9. Neural Networks

10. Ensemble Modeling

11. Presenting Results and Writing Data Mining Reports

12. Principal Component Analysis

13. Cluster Analysis

Part III Advanced Data Mining Methods

14. Random Forest

15. Gradient Boosting

16. Bayesian Networks

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Tags: Dothang Truong, Data Science, Machine Learning, Non Programmers, SAS Enterprise Miner