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Terence Tao Publisher: Hindustan Book Agency Year: 2014 Call Number NATIONAL INSTITUTE OF ADVANCED STUDIES LIBRARY NEW ARRIVALS 13 February 2019 SL.No TITLE ABSTRACT 1 Analysis Vol.1 This two-volume introduction to real analysis is intended for honours undergraduates, who have already been exposed to calculus. The emphasis is on rigour and on foundations. The course material is deeply intertwined with the exercises, as it is intended for the Author: Terence Tao student to actively learn the material and to practice thinking and writing rigorously. Publisher: Hindustan Book Agency Year: 2014 Related URL: https://www.amazon.in/Analysis-v-1-Terence-Tao/dp/8185931623 Call Number: 515 TAO 17263 Recommended by: Dr. Nithin Nagaraj 2 Biostatistical Analysis Zar’s Biostatistical Analysis, Fifth Edition, is the ideal textbook for graduate and undergraduate students seeking practical coverage of statistical analysis methods used by researchers to collect, summarize, analyze and draw conclusions from biological research. The Author: Jerrold H. Zar latest edition of this best-selling textbook is both comprehensive and easy to read. It is suitable as an introduction for beginning students and as a comprehensive reference book for biological researchers and for advanced students. Publisher: Pearson Year: 2013 This book is appropriate for a one- or two-semester, junior or graduate-level course in biostatistics, biometry, quantitative biology, or statistics, and assumes a prerequisite of algebra. Call Number: 570.15195 ZAR Official URL: https://www.pearson.com/us/higher-education/program/Zar-Biostatistical-Analysis-5th-Edition/PGM263783.html 17264 Recommended by: Dr. Nithin Nagaraj 3 Convex Optimization Convex optimization problems arise frequently in many different fields. This book provides a comprehensive introduction to the subject, and shows in detail how such problems can be solved numerically with great efficiency. The book begins with the basic Author: Stephen Boyd elements of convex sets and functions, and then describes various classes of convex optimization problems. Duality and approximation techniques are then covered, as are statistical estimation techniques. Various geometrical problems are then presented, Publisher: Cambridge University Press and there is detailed discussion of unconstrained and constrained minimization problems, and interior-point methods. The focus of Year: 2004 the book is on recognizing convex optimization problems and then finding the most appropriate technique for solving them. It contains many worked examples and homework exercises and will appeal to students, researchers and practitioners in fields such as Call Number: 519.6 engineering, computer science, mathematics, statistics, finance and economics. BOY 17265 Related URL: https://www.amazon.in/Convex-Optimization-Stephen-Boyd/dp/0521833787 Recommended by: Dr. Nithin Nagaraj 4 Deep Learning An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. "Written by three experts in the field, Deep Learning is the only Author: Ian Goodfellow comprehensive book on the subject." -Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of Publisher: MIT Press concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally Year: 2016 specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of Call Number: 006.31 topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, GOO probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, 17266 sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, Recommended by: Dr. Nithin Nagaraj covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors. Related URL: https://www.amazon.in/Deep-Learning-Ian- Goodfellow/dp/0262035618/ref=sr_1_1?s=books&ie=UTF8&qid=1550050585&sr=1- 1&keywords=deep+learning+by+ian+goodfellow 5 Elementary Linear Algebra When it comes to learning linear algebra, engineers trust Anton. The tenth edition presents the key concepts and topics along with engaging and contemporary applications. The chapters have been reorganized to bring up some of the more abstract topics and make the material more accessible. More theoretical exercises at all levels of difficulty are integrated throughout the pages, including Author: Howard Anton true/false questions that address conceptual ideas. New marginal notes provide a fuller explanation when new methods and complex Publisher: Wiley India logical steps are included in proofs. Small-scale applications also show how concepts are applied to help engineers develop their Year: 2015 mathematical reasoning. Call Number: 512.5 Related URL: https://www.amazon.com/Elementary-Linear-Algebra-Howard-Anton/dp/0470458216 ANT 17267 Recommended by: Dr. Nithin Nagaraj 6 Introduction to Applied Linear Algebra: This groundbreaking textbook combines straightforward explanations with a wealth of practical examples to offer an innovative Vectors, Matrices, and Least Squares approach to teaching linear algebra. Requiring no prior knowledge of the subject, it covers the aspects of linear algebra - vectors, matrices, and least squares - that are needed for engineering applications, discussing examples across data science, machine learning and artificial intelligence, signal and image processing, tomography, navigation, control, and finance. The numerous practical Author: Stephen Boyd & Lieven exercises throughout allow students to test their understanding and translate their knowledge into solving real-world problems, with Vandenberghe lecture slides, additional computational exercises in Julia and MATLAB®, and data sets accompanying the book online. Suitable for Publisher: Cambridge University Press both one-semester and one-quarter courses, as well as self-study, this self-contained text provides beginning students with the Year: 2018 foundation they need to progress to more advanced study. Call Number: 512.5 Related URL: https://www.amazon.com/Introduction-Applied-Linear-Algebra-Matrices/dp/1316518965 BOY 17268 Recommended by: Dr. Nithin Nagaraj 7 Introduction to Data Compression Introduction to Data Compression, Fourth Edition, is a concise and comprehensive guide to the art and science of data compression. This new edition includes all the cutting edge updates the reader will need during the work day and in class. It provides an extensive Author: Khalid Sayood introduction to the theory underlying today’s compression techniques with detailed instruction for their applications using several examples to explain the concepts. Publisher: Morgan Kaufmann Year: 2012 Encompassing the entire field of data compression, this book covers lossless and lossy compression, Huffman coding, arithmetic coding, dictionary techniques, context based compression, scalar and vector quantization. New to this fourth edition is a more Call Number: 006.746 detailed description of the JPEG 2000 standard as well as speech coding for internet applications. A source code is also provided via SAY a companion web site that gives readers the opportunity to build their own algorithms, choose and implement techniques in their own 17269 applications. Official URL: https://www.elsevier.com/books/introduction-to-data-compression/sayood/978-0-12-415796-5 Recommended by: Dr. Nithin Nagaraj 8 Introduction to Machine Learning The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including systems that analyze past sales data to predict customer behavior, Author: Ethem Alpaydin optimize robot behavior so that a task can be completed using minimum resources, and extract knowledge from bioinformatics data. Introduction to Machine Learning is a comprehensive textbook on the subject, covering a broad array of topics not usually included Publisher: MIT Press in introductory machine learning texts. Subjects include supervised learning; Bayesian decision theory; parametric, semi-parametric, Year: 2014 and nonparametric methods; multivariate analysis; hidden Markov models; reinforcement learning; kernel machines; graphical models; Bayesian estimation; and statistical testing. Call Number: 006.31 ALP Machine learning is rapidly becoming a skill
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