Introduction to Data Science, Das A.K., Bora M., Dhure V.
This textbook serves as a comprehensive and meticulously structured guide to gain knowledge in Data Science. It begins with a robust “Introduction” to Data Science, covering its benefits, evolution, process, roles, applications, and crucial ethical considerations like data privacy and security. It then delves into the essential “Basic Statistical Foundation for Data Science,” explaining measures of central tendency and dispersion, probability theory, various distributions, sampling theory, and hypothesis testing.

Characteristics of Data Warehouse.
Subject oriented: Data is organized in data warehouse based on a specific subject area. It results in faster query processing as the unwanted subjects are excluded from the analysis. The “sales”, “customers”, or “products” are examples of chosen subjects.
Integrated: Data from various sources are integrated in a sequential manner in data warehouse. All discrepancies related to naming conventions and representations of data value are eliminated in a data warehouse. Data in data warehouse is reliable, relevant, consistent ensuring only quality data is stored. Non-volatile: Data is stored in read-only format and remains unaffected over time. Typical data manipulation operations such as insertion, deletion and updation that occur in a normal relational database management system (RDBMS) do not happen in a data warehouse setting.
Contents.
About Pearson.
Title Page.
Table of Contents.
Foreword.
Preface.
Acknowledgements.
About the Authors.
Model Syllabus for Introduction to Data Science.
1. Introduction.
2. Basic Statistical Foundation for Data Science.
3. Data Acquisition and Integration.
4. Exploratory Data Analysis (EDA).
5. Data Preparation.
6. Feature Engineering.
7. Processing Text Data.
8. Model Creation and Validation.
9. Handling Large Datasets.
10. Data Warehousing and Data Mining.
Appendix: Case Study – Prediction & Reasons for Employees Attrition.
Model Question Paper - Set 1.
Model Question Paper - Set 2.
Index Credit Copyright.
Купить .
Теги: учебник по искусствоведению :: искусствоведение :: искусство :: Das :: Bora :: Dhure









