WILEY

https://onlinelibrary.wiley.com/

Call For Chapters

Edited Book "Advances in Data Science and Analytics"

FULL CHAPTER SUBMISSION : 29/05/2021

AMAZON GOOD READS GOOGLE.BOOKS AMAZON.UK BLACKWELLS.CO.UK DYMOCKS.COM.AU

About Book: This book will provide the contents of Advances in Data Science and Analytics Concept and Paradigm with practical approach. Topics to be covered - Components of DataScience - Machine Learning, Big Data, Business Intelligence, Types of Analytics - Descriptive Analytics. Diagnostic Analytics, Predictive Analytics, Prescriptive Analytics, Mathematics for Data Science, Data Visualization techniques - Understanding and Visualizing Data, Data Visualization in Tableau, Decision Making and Predictive Analysis - Implementing Scientific Decision Making, Using Predictive Data Analysis, Data Modeling and Optimization, Machine Learning, Regression Techniques, Data exploration, Evaluation methods, Classification Techniques, Clustering Techniques, Anomaly Detection, Dimensionality Reduction, Association Rule Learning, Deep Learning, Neural Networks, Big Data Analytics, Data Science with R, Python for Data Science, Building a Data Team, Data Processing, Data Storage, Data Privacy and security, Bayesian Networks. Case studies..etc ..

For Any queries E-mail: callforchaptersnm@gmail.com

Table of Contents (Not Limited to)

Components of DataScience:

· Machine Learning

· Big Data

· Business Intelligence

Four types of Analytics:

· Descriptive Analytics.

· Diagnostic Analytics.

· Predictive Analytics.

· Prescriptive Analytics.

Introduction to Data Science

· What is Data Science and why is it so important?

· Overview of Data Science and Analytics

· Mathematics for Data Science

· Introduction to Python and R

· Case Study

Data Visualization techniques

· Understanding and Visualizing Data

· Data Visualization in Tableau

Decision Making and Predictive Analysis

· Implementing Scientific Decision Making

· Using Predictive Data Analysis

· Case Study

Data Modeling and Optimization

· Modeling Uncertainty and Risk

· Optimization and Modeling Simultaneous Decisions

· Case Study

Machine Learning (Supervised Learning)

· Regression Techniques

· Data exploration

· Evaluation methods

· Classification Techniques

· Case Study

Machine Learning (Unsupervised Learning)

· Clustering Techniques

· Anomaly Detection

· Dimensionality Reduction

· Association Rule Learning

· Hands-on on clustering

· Hands-on association rule mining

· Hands-on dimensionality reduction

· Hands-on anomaly detection

· Case Study

Deep Learning

· Neural Networks

· Case Study

Big Data Analytics

· Introduction to Big data and Hadoop

· HDFS and YARN, MapReduce and Sqoop

· Hive and Impala

· Apache Flume and HBase

· Pig, Apache Spark

· Spark RDD Optimization Techniques

· Spark Algorithm, Spark SQL

· Case Study

Data Science with R

Python for Data Science

Building a Data Team

Data Processing

Data Storage

Data Privacy and security

Bayesian Networks

Association Rules Learning

Clustering

With analytical case studies Based on Domains.

Advanced Tools to support Data Science and Analytics

Statistics for Data Science

· Probability Theory

· Statistical Inference

· Sampling Theory

· Hypothesis Testing

· Regression Analysis

Mathematical Methods for Data Science

· Calculus

· Linear Algebra

· Decision Theory

Data Representation and Visualization

· Exploring Data

· Finding Relationships among Variables

· Graphing Data

· bar, pie and fever charts

· heat maps

· Correlation and Covariance

· Pivot Tables

Econometric Methods

· Time Series Analysis

· GARCH Models

· Fixed Effects Estimation

· Random Effects Estimation

Categorical Data Analysis

· Types of categorical data

· Generalized linear models

· Contingency tables

· Simple and multinomial logistic regression models

Optimization

· Linear Programming

· Integer Programming

· Multi-criteria Optimization

· Goal Programming

· AHP (Analytic Hierarchy Process)

· Data Envelopment Analysis (DEA)

Stochastic Processes and Simulation

· Random Variables and Distributions

· Monte Carlo Simulation

· Discrete Event Simulation

· Variance Reduction Techniques

Decision Support systems and Actionable Intelligence

· ERP systems

· SCM and CRM systems

· CRISP-DM model

· Insights to actions in an omnichannel environment

Big data storage and analysis

· Structured, semi-structured and unstructured data

· In-memory storage and NoSQL

· Distributed processing: Hadoop and MapReduce

· Complex events and stream analysis

• Publisher : John Wiley & Sons Inc (2 October 2022)

• Language : English

• Hardcover : 350 pages

• ISBN-10 : 111979188X

• ISBN-13 : 978-1119791881

AMAZON GOOD READS GOOGLE.BOOKS AMAZON.UK BLACKWELLS.CO.UK DYMOCKS.COM.AU

Full Chapter Submission: 29/05/2021

NO PUBLICATION/PROCESSING FEE, ITS FREE