Computer Science & Information Management

Statistics for Data and Predictive Analysis
Editors: Dr. Sunipa Roy
Prof. Rajat Subhra Chakraborty
Prof. Angsuman Sarkar

Not for sale at this time
Statistics for Data and Predictive Analysis

CALL FOR BOOK CHAPTERS
Pub Date: TBA
Hardback Price: TBA
Hard ISBN: 
Pages: TBA
Binding Type: 

CALL FOR BOOK CHAPTERS

Data science and machine learning is an interdisciplinary subject that uses the basic concepts of statistics, data analysis, and machine learning algorithms to understand and analyze various problems and phenomena with respect to a large set of data. This book includes various theories and techniques from statistics and tools from Python.

The aim of this volume is to expose students to the elemental areas of applied statistics, data visualization predictive modeling, and machine learning to get them absorbed in various sectors such as business, marketing, supply chain, manufacturing, genomics, healthcare, banking, etc., using hands-on experience. Another aim is to produce agile and skilled professionals to understand, collect, extract, analyze, and predict the given set of data to solve the major problems through real-time data analysis. In addition to that, machine learning is important because it gives enterprises a view of trends in customer behavior and business operational patterns, as well as supports the development of new products. Many of today‘s leading companies, such as Facebook, Google, and Uber, make machine learning a central part of their operations.

Positions in data analytics and machine learning professional are the most sought-after jobs worldwide. Therefore, this is the right time to pursue this study.

We invite submission of book chapters to editors covering the following topics:

I. Introduction
II. Collection, Representation, and Pre-Processing of Data
III. Sampling Theory
IV. Measures of Dispersion
V. Hypothesis testing, Tabulation and Processing of Data
VI. Correlation and Regression
VII. Dimensionality Reduction
VIII. Classification IX .Clustering
X. Random Forest
XI. Artificial Neural Network
XII. Data Analysis using Python
XIII. Machine Learning Models: Using Python

The original full-length chapters/communications are invited for submission. Contributors are advised to email to either of the book editors via email. The manuscripts will be peer-reviewed. Earlier published works or those submitted for publications in other journals/conference proceedings will not be considered. The language of the manuscript is English.

MANUSCRIPT SUBMISSION
All manuscripts must be 100% original and unpublished which should be prepared according to the Publisher‘s guidelines, available at https://www.appleacademicpress.com/publishwithus. Submit your abstract on the topic mentioned above to one of the editors. After scrutiny, the status will be communicated to the corresponding author. If the status is ‘Accepted,‘ authors will have to submit the full-length chapter as a single file both in MS word or PDF format by EMAIL to one of the book editors. All chapters submitted to this book will be subject toa strict peer review to ensure the high quality of the chapters. Please make sure in the cover letter that the submitted chapter has not been published previously and is not currently submitted for review to any other book or journals/conference proceedings and will not be submitted elsewhere before a decision is made by the review committee.



KEY DATES

Abstract submission deadline: 30 December 2024


About the Authors / Editors:
Editors: Dr. Sunipa Roy
Associate Professor, Guru Nanak Institute of Technology, Kolkata, India
Email: suniparoy4@gmail.com


Prof. Rajat Subhra Chakraborty
Professor, IIT Kharagpur, Computer Science and Engineering, Kharagpur, India
Email: rschakraborty@gmail.com


Prof. Angsuman Sarkar
Professor, Kalyani Government Engineering College, Nadia, West Bengal, India
Email:angsumansarkar@gmail.com





Follow us for the latest from Apple Academic Press:
Copyright © 2025 Apple Academic Press Inc. All Rights Reserved.