Jugal K. Kalita's Books

Fundamentals of Data Science

Theory and Practice

By: Jugal K. Kalita,Dhruba K. Bhattacharyya,Swarup Roy

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Fundamentals of Data Science

Theory and Practice

By: Jugal K. Kalita,Dhruba K. Bhattacharyya,Swarup Roy

Fundamentals of Data Science: Theory and Practice presents basic and advanced concepts in data science along with real-life applications. The book provides students, researchers and professionals at different levels a good understanding of the concepts of data science, machine learning, data mining and analytics. Users will find the authors' research experiences and achievements in data science applications, along with in-depth discussions on topics that are essential for data science projects, including pre-processing, that is carried out before applying predictive and descriptive data analysis tasks and proximity measures for numeric, categorical and mixed-type data. The book's authors include a systematic presentation of many predictive and descriptive learning algorithms, including recent developments that have successfully handled large datasets with high accuracy. In addition, a number of descriptive learning tasks are included. - Presents the foundational concepts of data science along with advanced concepts and real-life applications for applied learning - Includes coverage of a number of key topics such as data quality and pre-processing, proximity and validation, predictive data science, descriptive data science, ensemble learning, association rule mining, Big Data analytics, as well as incremental and distributed learning - Provides updates on key applications of data science techniques in areas such as Computational Biology, Network Intrusion Detection, Natural Language Processing, Software Clone Detection, Financial Data Analysis, and Scientific Time Series Data Analysis - Covers computer program code for implementing descriptive and predictive algorithms

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Page Count

336

Publisher

Elsevier

Published Date

ISBN 10

0323972632

ISBN 13

9780323972635

Network Traffic Anomaly Detection and Prevention

Concepts, Techniques, and Tools

By: Monowar H. Bhuyan,Dhruba K. Bhattacharyya,Jugal K. Kalita

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Network Traffic Anomaly Detection and Prevention

Concepts, Techniques, and Tools

By: Monowar H. Bhuyan,Dhruba K. Bhattacharyya,Jugal K. Kalita

This indispensable text/reference presents a comprehensive overview on the detection and prevention of anomalies in computer network traffic, from coverage of the fundamental theoretical concepts to in-depth analysis of systems and methods. Readers will benefit from invaluable practical guidance on how to design an intrusion detection technique and incorporate it into a system, as well as on how to analyze and correlate alerts without prior information. Topics and features: introduces the essentials of traffic management in high speed networks, detailing types of anomalies, network vulnerabilities, and a taxonomy of network attacks; describes a systematic approach to generating large network intrusion datasets, and reviews existing synthetic, benchmark, and real-life datasets; provides a detailed study of network anomaly detection techniques and systems under six different categories: statistical, classification, knowledge-base, cluster and outlier detection, soft computing, and combination learners; examines alert management and anomaly prevention techniques, including alert preprocessing, alert correlation, and alert post-processing; presents a hands-on approach to developing network traffic monitoring and analysis tools, together with a survey of existing tools; discusses various evaluation criteria and metrics, covering issues of accuracy, performance, completeness, timeliness, reliability, and quality; reviews open issues and challenges in network traffic anomaly detection and prevention. This informative work is ideal for graduate and advanced undergraduate students interested in network security and privacy, intrusion detection systems, and data mining in security. Researchers and practitioners specializing in network security will also find the book to be a useful reference.

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Page Count

278

Publisher

Springer

Published Date

ISBN 10

3319651889

ISBN 13

9783319651880

On Perl

Perl for Students and Professionals

By: Jugal Kalita

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On Perl

Perl for Students and Professionals

By: Jugal Kalita

The book has an introductory chapter that gets the reader started quickly with programming in Perl. The initial part of the book discusses Perl expressions, statements, control flow, built-in data types such as arrays and hashes, and complex data structures built using references. On Perl has several chapters covering specialized topics. The chapter on socket-based network programming deals with forking and using fork to write complex interactive client-server programs. There is a chapter with in-depth discussion of CGI programming including error-handling and security issues that arise. The chapter on web-client programming deals with writing programs that access Web pages, fill up GET and POST forms, handle cookies and redirected Web pages. The book has several unique chapters not found in any other book on Perl in the market. The chapter on security discusses hashes such as MD5, message authentication codes (MACs), digital signature schemes, and encryption techniques such as DES, Rijndael, and RSA. Other chapters deal with writing recursive programs that work with files and directories; this chapter also discusses predefined modules that deal with portability in file names and paths across operating systems, recursive traversal of file hierarchies and tarring and untarring of filles. The chapter on functional programming illustrates that Perl functions are first-class, can be used to write closures and can be composed to form more complex functions. In particular, this can be useful for programming in artificial intelligence.

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Page Count

664

Publisher

Universal-Publishers

Published Date

ISBN 10

158112550X

ISBN 13

9781581125504

Gene Expression Data Analysis

A Statistical and Machine Learning Perspective

By: Pankaj Barah,Dhruba Kumar Bhattacharyya,Jugal Kumar Kalita

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Gene Expression Data Analysis

A Statistical and Machine Learning Perspective

By: Pankaj Barah,Dhruba Kumar Bhattacharyya,Jugal Kumar Kalita

Development of high-throughput technologies in molecular biology during the last two decades has contributed to the production of tremendous amounts of data. Microarray and RNA sequencing are two such widely used high-throughput technologies for simultaneously monitoring the expression patterns of thousands of genes. Data produced from such experiments are voluminous (both in dimensionality and numbers of instances) and evolving in nature. Analysis of huge amounts of data toward the identification of interesting patterns that are relevant for a given biological question requires high-performance computational infrastructure as well as efficient machine learning algorithms. Cross-communication of ideas between biologists and computer scientists remains a big challenge. Gene Expression Data Analysis: A Statistical and Machine Learning Perspective has been written with a multidisciplinary audience in mind. The book discusses gene expression data analysis from molecular biology, machine learning, and statistical perspectives. Readers will be able to acquire both theoretical and practical knowledge of methods for identifying novel patterns of high biological significance. To measure the effectiveness of such algorithms, we discuss statistical and biological performance metrics that can be used in real life or in a simulated environment. This book discusses a large number of benchmark algorithms, tools, systems, and repositories that are commonly used in analyzing gene expression data and validating results. This book will benefit students, researchers, and practitioners in biology, medicine, and computer science by enabling them to acquire in-depth knowledge in statistical and machine-learning-based methods for analyzing gene expression data. Key Features: An introduction to the Central Dogma of molecular biology and information flow in biological systems A systematic overview of the methods for generating gene expression data Background knowledge on statistical modeling and machine learning techniques Detailed methodology of analyzing gene expression data with an example case study Clustering methods for finding co-expression patterns from microarray, bulkRNA, and scRNA data A large number of practical tools, systems, and repositories that are useful for computational biologists to create, analyze, and validate biologically relevant gene expression patterns Suitable for multidisciplinary researchers and practitioners in computer science and the biological sciences

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Page Count

276

Publisher

CRC Press

Published Date

ISBN 10

1000425754

ISBN 13

9781000425758

Book's by Jugal K. Kalita

Fundamentals of Data Science

Fundamentals of Data Science

Network Traffic Anomaly Detection and Prevention

Network Traffic Anomaly Detection and Prevention

On Perl

On Perl

Gene Expression Data Analysis

Gene Expression Data Analysis

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