Data science : Vijay Kotu and Balachandre Deshpande. concepts and practice /

By:

Kotu, Vijay

Contributor(s):

Deshpande, Balachandre

text

Media type:

unmediated

Carrier type:

volume

ISBN:

9780128147610 (pbk)

Subject(s):

DDC classification:

23 006.312 K84 2019

Contents:

1. Introduction 2. Data Science Process 3. Data Exploration4. Classification 5. Deep Learning 6. Regression Methods 7. Association Analysis 8. Recommendation Engines 9. Clustering 10. Text Mining (renamed to: Natural Language Processing) 11. Time Series Forecasting 12. Anomaly Detection 13. Feature Selection14. Model Evaluation 15. Efficient Model Execution 16. Getting Started with RapidMiner

Summary: Learn the basics of Data Science through an easy to understand conceptual framework and immediately practice using RapidMiner platform. Whether you are brand new to data science or working on your tenth project, this book will show you how to analyze data, uncover hidden patterns and relationships to aid important decisions and predictions. Data Science has become an essential tool to extract value from data for any organization that collects, stores and processes data as part of its operations. This book is ideal for business users, data analysts, business analysts, engineers, and analytics professionals and for anyone who works with data. You'll be able to: Gain the necessary knowledge of different data science techniques to extract value from data. Master the concepts and inner workings of 30 commonly used powerful data science algorithms. Implement step-by-step data science process using using RapidMiner, an open source GUI based data science platform Data Science techniques covered: Exploratory data analysis, Visualization, Decision trees, Rule induction, k-nearest neighbors, Naive Bayesian classifiers, Artificial neural networks, Deep learning, Support vector machines, Ensemble models, Random forests, Regression, Recommendation engines, Association analysis, K-Means and Density based clustering, Self organizing maps, Text mining, Time series forecasting, Anomaly detection, Feature selection and more...

Holdings
Item type	Current library	Collection	Call number	Status	Barcode
Books	College Library General Circulation Section	GC	GC 006.312 K84 2019 (Browse shelf(Opens below))	Available	HNU001217

Includes index.

Learn the basics of Data Science through an easy to understand conceptual framework and immediately practice using RapidMiner platform. Whether you are brand new to data science or working on your tenth project, this book will show you how to analyze data, uncover hidden patterns and relationships to aid important decisions and predictions. Data Science has become an essential tool to extract value from data for any organization that collects, stores and processes data as part of its operations. This book is ideal for business users, data analysts, business analysts, engineers, and analytics professionals and for anyone who works with data. You'll be able to: Gain the necessary knowledge of different data science techniques to extract value from data. Master the concepts and inner workings of 30 commonly used powerful data science algorithms. Implement step-by-step data science process using using RapidMiner, an open source GUI based data science platform Data Science techniques covered: Exploratory data analysis, Visualization, Decision trees, Rule induction, k-nearest neighbors, Naive Bayesian classifiers, Artificial neural networks, Deep learning, Support vector machines, Ensemble models, Random forests, Regression, Recommendation engines, Association analysis, K-Means and Density based clustering, Self organizing maps, Text mining, Time series forecasting, Anomaly detection, Feature selection and more...

College of Engineering and Computer Studies Bachelor of Science in Computer Science