Jugal Kalita's Books

Machine Learning

Theory and Practice

By: Jugal Kalita

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Machine Learning: Theory and Practice provides an introduction to the most popular methods in machine learning. The book covers regression including regularization, tree-based methods including Random Forests and Boosted Trees, Artificial Neural Networks including Convolutional Neural Networks (CNNs), reinforcement learning, and unsupervised learning focused on clustering. Topics are introduced in a conceptual manner along with necessary mathematical details. The explanations are lucid, illustrated with figures and examples. For each machine learning method discussed, the book presents appropriate libraries in the R programming language along with programming examples. Features: Provides an easy-to-read presentation of commonly used machine learning algorithms in a manner suitable for advanced undergraduate or beginning graduate students, and mathematically and/or programming-oriented individuals who want to learn machine learning on their own. Covers mathematical details of the machine learning algorithms discussed to ensure firm understanding, enabling further exploration Presents worked out suitable programming examples, thus ensuring conceptual, theoretical and practical understanding of the machine learning methods. This book is aimed primarily at introducing essential topics in Machine Learning to advanced undergraduates and beginning graduate students. The number of topics has been kept deliberately small so that it can all be covered in a semester or a quarter. The topics are covered in depth, within limits of what can be taught in a short period of time. Thus, the book can provide foundations that will empower a student to read advanced books and research papers.

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Page Count

311

Publisher

CRC Press

Published Date

ISBN 10

100081825X

ISBN 13

9781000818253

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

Machine Learning

Theory and Practice

By: Jugal Kalita

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Machine Learning

Theory and Practice

By: Jugal Kalita

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Page Count

299

Publisher

CRC Press

Published Date

ISBN 10

1000818225

ISBN 13

9781000818222

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 biological sciences

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Page Count

379

Publisher

CRC Press

Published Date

ISBN 10

1000425738

ISBN 13

9781000425734

Network Anomaly Detection

A Machine Learning Perspective

By: Dhruba Kumar Bhattacharyya,Jugal Kumar Kalita

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Network Anomaly Detection

A Machine Learning Perspective

By: Dhruba Kumar Bhattacharyya,Jugal Kumar Kalita

With the rapid rise in the ubiquity and sophistication of Internet technology and the accompanying growth in the number of network attacks, network intrusion detection has become increasingly important. Anomaly-based network intrusion detection refers to finding exceptional or nonconforming patterns in network traffic data compared to normal behavi

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Page Count

364

Publisher

CRC Press

Published Date

ISBN 10

146658209X

ISBN 13

9781466582095

On Perl

Perl for Students and Professionals

By: Jugal Kalita

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On Perl

Perl for Students and Professionals

By: Jugal Kalita

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Page Count

664

Publisher

Universal-Publishers

Published Date

ISBN 10

158112550X

ISBN 13

9781581125504

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

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

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Solve jigsaw puzzle

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Page Count

276

Publisher

CRC Press

Published Date

ISBN 10

1000425754

ISBN 13

9781000425758

Book's by Jugal Kalita

Machine Learning

Machine Learning

On Perl

On Perl

Machine Learning

Machine Learning

Gene Expression Data Analysis

Gene Expression Data Analysis

Network Anomaly Detection

Network Anomaly Detection

On Perl

On Perl

Fundamentals of Data Science

Fundamentals of Data Science

Gene Expression Data Analysis

Gene Expression Data Analysis

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