Amita Pal's Books

Pattern Recognition

From Classical to Modern Approaches

By: Sankar K. Pal,Amita Pal

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Pattern Recognition

From Classical to Modern Approaches

By: Sankar K. Pal,Amita Pal

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635

Publisher

World Scientific

Published Date

ISBN 10

9810246846

ISBN 13

9789810246846

Concise Encyclopaedia of India

By: Amita Gupta

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Concise Encyclopaedia of India

By: Amita Gupta

The Present Book, Concise Encyclopaedia Of India, Is A Compendium Of Diverse Aspects Of India Which Is One Of The Oldest Civilisations With A Kaleidoscopic Variety, Rich Cultural Heritage And Multifaceted Socio-Economic Progress. The Idea Behind Bringing Out This Book Is To Help One And All In Understanding The Country And Its Unity In Diversity. In Its Three Volumes, The Encyclopaedia Encompasses A Remarkably Wide Range Of Topics Related To India Its History, Physiography, People, Population, National Symbols, National Leaders, Languages And Literatures, Art, Culture, Defence, Education, Economy, Polity, Foreign Policy And Relations, Scientific And Technological Developments, Law And Justice, Sports, Festivals, Transport, Communication And Related Activities. In Addition, A Profile Of All Its 28 States And 7 Union Territories Has Also Been Provided. Furthermore, It Provides An Accessible, Authoritative Account Of The Latest Developments Made In Varied Fields Alongwith The Data From The Central And State Governments, Their Establishments, Constitutional Bodies, Autonomous And Semi-Autonomous Bodies And The Like.The Book Is Comprehensive, Self-Contained And User-Friendly, As The Emphasis Throughout Is On Ensuring That Readers, Particularly Students, Receive Worthwhile, Authentic Information Instead Of Irrelevant And Outdated Details. It Will Definitely Prove An Invaluable Reference Book To Students Of Different Educational Levels And Candidates Preparing For Civil Services Examinations Or Other Competitive Exams And Interviews For Various Jobs. Besides Students, The Researchers, Executives In Government And Private Sector And Also The Common Man Will Find It Highly Informative.

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446

Publisher

Atlantic Publishers & Dist

Published Date

ISBN 10

8126906375

ISBN 13

9788126906376

Cultural Landscapes of India

Imagined, Enacted, and Reclaimed

By: Amita Sinha

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Cultural Landscapes of India

Imagined, Enacted, and Reclaimed

By: Amita Sinha

Most people view cultural heritage sites as static places, frozen in time. In Cultural Landscapes in India, Amita Sinha subverts the idea of heritage as static and examines the ways that landscapes influence culture and that culture influences landscapes. The book centers around imagining, enacting, and reclaiming landscapes as subjects and settings of living cultural heritage. Drawing on case studies from different regions of India, Sinha offers new interpretations of links between land and culture using different ways of seeing—transcendental, romantic, and utilitarian. The idea of cultural landscape can be seen in ancient practices such as circumambulation and immersion in bodies of water that sustain engagement with natural elements. Pilgrim towns, medieval forts, religious sites, and contemporary memorial parks are sites of memory where myth and history converge. Engaging with these spaces allows us to reconstruct collective memory and reclaim not only historic landscapes, but ways of seeing, making, and remembering. Cultural Landscapes in India makes the case for reclaiming iconic landscapes and rethinking conventional approaches to conservation that take into consideration performative landscape as heritage.

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272

Publisher

University of Pittsburgh Press

Published Date

ISBN 10

0822987864

ISBN 13

9780822987864

Deep Learning with TensorFlow 2 and Keras

Regression, ConvNets, GANs, RNNs, NLP, and more with TensorFlow 2 and the Keras API, 2nd Edition

By: Antonio Gulli,Amita Kapoor,Sujit Pal

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Deep Learning with TensorFlow 2 and Keras

Regression, ConvNets, GANs, RNNs, NLP, and more with TensorFlow 2 and the Keras API, 2nd Edition

By: Antonio Gulli,Amita Kapoor,Sujit Pal

Build machine and deep learning systems with the newly released TensorFlow 2 and Keras for the lab, production, and mobile devices Key FeaturesIntroduces and then uses TensorFlow 2 and Keras right from the startTeaches key machine and deep learning techniquesUnderstand the fundamentals of deep learning and machine learning through clear explanations and extensive code samplesBook Description Deep Learning with TensorFlow 2 and Keras, Second Edition teaches neural networks and deep learning techniques alongside TensorFlow (TF) and Keras. You’ll learn how to write deep learning applications in the most powerful, popular, and scalable machine learning stack available. TensorFlow is the machine learning library of choice for professional applications, while Keras offers a simple and powerful Python API for accessing TensorFlow. TensorFlow 2 provides full Keras integration, making advanced machine learning easier and more convenient than ever before. This book also introduces neural networks with TensorFlow, runs through the main applications (regression, ConvNets (CNNs), GANs, RNNs, NLP), covers two working example apps, and then dives into TF in production, TF mobile, and using TensorFlow with AutoML. What you will learnBuild machine learning and deep learning systems with TensorFlow 2 and the Keras APIUse Regression analysis, the most popular approach to machine learningUnderstand ConvNets (convolutional neural networks) and how they are essential for deep learning systems such as image classifiersUse GANs (generative adversarial networks) to create new data that fits with existing patternsDiscover RNNs (recurrent neural networks) that can process sequences of input intelligently, using one part of a sequence to correctly interpret anotherApply deep learning to natural human language and interpret natural language texts to produce an appropriate responseTrain your models on the cloud and put TF to work in real environmentsExplore how Google tools can automate simple ML workflows without the need for complex modelingWho this book is for This book is for Python developers and data scientists who want to build machine learning and deep learning systems with TensorFlow. This book gives you the theory and practice required to use Keras, TensorFlow 2, and AutoML to build machine learning systems. Some knowledge of machine learning is expected.

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647

Publisher

Packt Publishing Ltd

Published Date

ISBN 10

1838827722

ISBN 13

9781838827724

Essentials of Microbiology for Dental Students - E-Book

By: Amita Jain,Parul Jain

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Essentials of Microbiology for Dental Students - E-Book

By: Amita Jain,Parul Jain

This book presents a thorough and systematic approach of microbiology in a very clear,concise, simplified and easily understandable manner. The text is amply illustrated by largenumber of figures, flowcharts, tables and boxes. This will help not only in understanding theconcepts to clear the professional exams but will also teach the importance and application ofmicrobiology in clinical practice.• Focus on clinical and laboratory aspects of infectious diseases covering bacterial, tubercular,viral, parasitic and fungal infections.• Organization of the text into sections helps to recollect the facts easily.• Chapter outline in the beginning of each chapter helps to facilitate self-learning by thestudents.• Syndromic approach to common syndromes highlights the important causes and laboratorydiagnostic approach.• Flowcharts and line diagrams represent the diagnostic procedures and life cycles.• Questions given at the end of chapters for self-assessment of topics.• Multiple choice questions section-by-section at the end of the book for self-assessment ofthe topics studied.Online Resources at www.medenact.com• Complimentary access to full e-book.• Procedural animations.

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421

Publisher

Elsevier Health Sciences

Published Date

ISBN 10

8131267202

ISBN 13

9788131267202

Deep Learning with TensorFlow and Keras

Build and deploy supervised, unsupervised, deep, and reinforcement learning models

By: Amita Kapoor,Antonio Gulli,Sujit Pal,Francois Chollet

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Deep Learning with TensorFlow and Keras

Build and deploy supervised, unsupervised, deep, and reinforcement learning models

By: Amita Kapoor,Antonio Gulli,Sujit Pal,Francois Chollet

Build cutting edge machine and deep learning systems for the lab, production, and mobile devices Key FeaturesUnderstand the fundamentals of deep learning and machine learning through clear explanations and extensive code samplesImplement graph neural networks, transformers using Hugging Face and TensorFlow Hub, and joint and contrastive learningLearn cutting-edge machine and deep learning techniquesBook Description Deep Learning with TensorFlow and Keras teaches you neural networks and deep learning techniques using TensorFlow (TF) and Keras. You'll learn how to write deep learning applications in the most powerful, popular, and scalable machine learning stack available. TensorFlow 2.x focuses on simplicity and ease of use, with updates like eager execution, intuitive higher-level APIs based on Keras, and flexible model building on any platform. This book uses the latest TF 2.0 features and libraries to present an overview of supervised and unsupervised machine learning models and provides a comprehensive analysis of deep learning and reinforcement learning models using practical examples for the cloud, mobile, and large production environments. This book also shows you how to create neural networks with TensorFlow, runs through popular algorithms (regression, convolutional neural networks (CNNs), transformers, generative adversarial networks (GANs), recurrent neural networks (RNNs), natural language processing (NLP), and graph neural networks (GNNs)), covers working example apps, and then dives into TF in production, TF mobile, and TensorFlow with AutoML. What you will learnLearn how to use the popular GNNs with TensorFlow to carry out graph mining tasksDiscover the world of transformers, from pretraining to fine-tuning to evaluating themApply self-supervised learning to natural language processing, computer vision, and audio signal processingCombine probabilistic and deep learning models using TensorFlow ProbabilityTrain your models on the cloud and put TF to work in real environmentsBuild machine learning and deep learning systems with TensorFlow 2.x and the Keras APIWho this book is for This hands-on machine learning book is for Python developers and data scientists who want to build machine learning and deep learning systems with TensorFlow. This book gives you the theory and practice required to use Keras, TensorFlow, and AutoML to build machine learning systems. Some machine learning knowledge would be useful. We don't assume TF knowledge.

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699

Publisher

Packt Publishing Ltd

Published Date

ISBN 10

1803245719

ISBN 13

9781803245713

TensorFlow Machine Learning Projects

Build 13 real-world projects with advanced numerical computations using the Python ecosystem

By: Ankit Jain,Armando Fandango,Amita Kapoor

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TensorFlow Machine Learning Projects

Build 13 real-world projects with advanced numerical computations using the Python ecosystem

By: Ankit Jain,Armando Fandango,Amita Kapoor

Implement TensorFlow's offerings such as TensorBoard, TensorFlow.js, TensorFlow Probability, and TensorFlow Lite to build smart automation projects Key FeaturesUse machine learning and deep learning principles to build real-world projectsGet to grips with TensorFlow's impressive range of module offeringsImplement projects on GANs, reinforcement learning, and capsule networkBook Description TensorFlow has transformed the way machine learning is perceived. TensorFlow Machine Learning Projects teaches you how to exploit the benefits—simplicity, efficiency, and flexibility—of using TensorFlow in various real-world projects. With the help of this book, you’ll not only learn how to build advanced projects using different datasets but also be able to tackle common challenges using a range of libraries from the TensorFlow ecosystem. To start with, you’ll get to grips with using TensorFlow for machine learning projects; you’ll explore a wide range of projects using TensorForest and TensorBoard for detecting exoplanets, TensorFlow.js for sentiment analysis, and TensorFlow Lite for digit classification. As you make your way through the book, you’ll build projects in various real-world domains, incorporating natural language processing (NLP), the Gaussian process, autoencoders, recommender systems, and Bayesian neural networks, along with trending areas such as Generative Adversarial Networks (GANs), capsule networks, and reinforcement learning. You’ll learn how to use the TensorFlow on Spark API and GPU-accelerated computing with TensorFlow to detect objects, followed by how to train and develop a recurrent neural network (RNN) model to generate book scripts. By the end of this book, you’ll have gained the required expertise to build full-fledged machine learning projects at work. What you will learnUnderstand the TensorFlow ecosystem using various datasets and techniquesCreate recommendation systems for quality product recommendationsBuild projects using CNNs, NLP, and Bayesian neural networksPlay Pac-Man using deep reinforcement learningDeploy scalable TensorFlow-based machine learning systemsGenerate your own book script using RNNsWho this book is for TensorFlow Machine Learning Projects is for you if you are a data analyst, data scientist, machine learning professional, or deep learning enthusiast with basic knowledge of TensorFlow. This book is also for you if you want to build end-to-end projects in the machine learning domain using supervised, unsupervised, and reinforcement learning techniques

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311

Publisher

Packt Publishing Ltd

Published Date

ISBN 10

1789132401

ISBN 13

9781789132403

Microbiology Practical Manual, 1st Edition-E-book

By: Amita Jain,Jyotsna Agarwal,Vimala Venkatesh

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Microbiology Practical Manual, 1st Edition-E-book

By: Amita Jain,Jyotsna Agarwal,Vimala Venkatesh

This book is a practical manual in Microbiology for 2nd year MBBS students. There is no standard book for practical exams in the market. This book will be a student's companion in their Microbiology practical class where they can read it, do their experiments as per directions given in book, and do their assignments. It would be a 'complete practical book' with tutorials at the beginning of each chapter helping the students understand the concepts. - Integrates practical & important theoretical concepts of Microbiology - Every chapter divided in a tutorial, practical exercise, spotters and assignments - Contains easy to reproduce diagrams during the practical exams - Important case-wise Viva questions at the end of each chapter - Sample cases at the end of each chapter for understanding the correlation It would be a 'complete practical book' with tutorials at the beginning of each chapter helping the students understand the concepts.

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Page Count

341

Publisher

Elsevier Health Sciences

Published Date

ISBN 10

8131253546

ISBN 13

9788131253540

TensorFlow 1.x Deep Learning Cookbook

Over 90 unique recipes to solve artificial-intelligence driven problems with Python

By: Antonio Gulli,Amita Kapoor

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TensorFlow 1.x Deep Learning Cookbook

Over 90 unique recipes to solve artificial-intelligence driven problems with Python

By: Antonio Gulli,Amita Kapoor

Take the next step in implementing various common and not-so-common neural networks with Tensorflow 1.x About This Book Skill up and implement tricky neural networks using Google's TensorFlow 1.x An easy-to-follow guide that lets you explore reinforcement learning, GANs, autoencoders, multilayer perceptrons and more. Hands-on recipes to work with Tensorflow on desktop, mobile, and cloud environment Who This Book Is For This book is intended for data analysts, data scientists, machine learning practitioners and deep learning enthusiasts who want to perform deep learning tasks on a regular basis and are looking for a handy guide they can refer to. People who are slightly familiar with neural networks, and now want to gain expertise in working with different types of neural networks and datasets, will find this book quite useful. What You Will Learn Install TensorFlow and use it for CPU and GPU operations Implement DNNs and apply them to solve different AI-driven problems. Leverage different data sets such as MNIST, CIFAR-10, and Youtube8m with TensorFlow and learn how to access and use them in your code. Use TensorBoard to understand neural network architectures, optimize the learning process, and peek inside the neural network black box. Use different regression techniques for prediction and classification problems Build single and multilayer perceptrons in TensorFlow Implement CNN and RNN in TensorFlow, and use it to solve real-world use cases. Learn how restricted Boltzmann Machines can be used to recommend movies. Understand the implementation of Autoencoders and deep belief networks, and use them for emotion detection. Master the different reinforcement learning methods to implement game playing agents. GANs and their implementation using TensorFlow. In Detail Deep neural networks (DNNs) have achieved a lot of success in the field of computer vision, speech recognition, and natural language processing. The entire world is filled with excitement about how deep networks are revolutionizing artificial intelligence. This exciting recipe-based guide will take you from the realm of DNN theory to implementing them practically to solve the real-life problems in artificial intelligence domain. In this book, you will learn how to efficiently use TensorFlow, Google's open source framework for deep learning. You will implement different deep learning networks such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Deep Q-learning Networks (DQNs), and Generative Adversarial Networks (GANs) with easy to follow independent recipes. You will learn how to make Keras as backend with TensorFlow. With a problem-solution approach, you will understand how to implement different deep neural architectures to carry out complex tasks at work. You will learn the performance of different DNNs on some popularly used data sets such as MNIST, CIFAR-10, Youtube8m, and more. You will not only learn about the different mobile and embedded platforms supported by TensorFlow but also how to set up cloud platforms for deep learning applications. Get a sneak peek of TPU architecture and how they will affect DNN future. By using crisp, no-nonsense recipes, you will become an expert in implementing deep learning techniques in growing real-world applications and research areas such as reinforcement learning, GANs, autoencoders and more. Style and approach This book consists of hands-on recipes where you'll deal with real-world problems. You'll execute a series of tasks as you walk through data mining challenges using TensorFlow 1.x. Your one-stop solution for common and not-so-common pain points, this is a book that you must have on the shelf.

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526

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Packt Publishing Ltd

Published Date

ISBN 10

1788291867

ISBN 13

9781788291866

Marxism

With and Beyond Marx

By: Amiya Bagchi,Amita Chatterjee

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Marxism

With and Beyond Marx

By: Amiya Bagchi,Amita Chatterjee

This book offers a unique re-conceptualization of Marxism in bringing together leading scholars across disciplines — history, philosophy, economics, politics, sociology, and literary and culture studies — into one comprehensive corpus. It demonstrates the engaging relevance of the perspectives and techniques of the analyses adopted by Karl Marx, Frederich Engels and contemporary Marxists, and will be immensely useful to scholars and researchers across social sciences as well as general readers interested in Marxism.

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238

Publisher

Routledge

Published Date

ISBN 10

1317561767

ISBN 13

9781317561767

Pattern Recognition

From Classical to Modern Approaches

By: Sankar K. Pal,Pal. Amita

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Pattern Recognition

From Classical to Modern Approaches

By: Sankar K. Pal,Pal. Amita

This volume, containing contributions by experts from all over the world, is a collection of 21 articles which present review and research material describing the evolution and recent developments of various pattern recognition methodologies, ranging from statistical, syntactic/linguistic, fuzzy-set-theoretic, neural, genetic-algorithmic and rough-set-theoretic to hybrid soft computing, with significant real-life applications. In addition, the book describes efficient soft machine learning algorithms for data mining and knowledge discovery. With a balanced mixture of theory, algorithms and applications, as well as up-to-date information and an extensive bibliography, Pattern Recognition: From Classical to Modern Approaches is a very useful resource. Contents: Pattern Recognition: Evolution of Methodologies and Data Mining (A Pal & S K Pal); Adaptive Stochastic Algorithms for Pattern Classification (M A L Thathachar & P S Sastry); Shape in Images (K V Mardia); Decision Trees for Classification: A Review and Some New Results (R Kothari & M Dong); Syntactic Pattern Recognition (A K Majumder & A K Ray); Fuzzy Sets as a Logic Canvas for Pattern Recognition (W Pedrycz & N Pizzi); Neural Network Based Pattern Recognition (V David Sanchez A); Networks of Spiking Neurons in Data Mining (K Cios & D M Sala); Genetic Algorithms, Pattern Classification and Neural Networks Design (S Bandyopadhyay et al.); Rough Sets in Pattern Recognition (A Skowron & R Swiniarski); Automated Generation of Qualitative Representations of Complex Objects by Hybrid Soft-Computing Methods (E H Ruspini & I S Zwir); Writing Speed and Writing Sequence Invariant On-line Handwriting Recognition (S-H Cha & S N Srihari); Tongue Diagnosis Based on Biometric Pattern Recognition Technology (K Wang et al.); and other papers. Readership: Graduate students, researchers and academics in pattern recognition.

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644

Publisher

World Scientific

Published Date

ISBN 10

981238653X

ISBN 13

9789812386533

Deep Learning with TensorFlow and Keras

Build and deploy supervised, unsupervised, deep, and reinforcement learning models

By: Amita Kapoor,Antonio Gulli,Sujit Pal,Francois Chollet

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Deep Learning with TensorFlow and Keras

Build and deploy supervised, unsupervised, deep, and reinforcement learning models

By: Amita Kapoor,Antonio Gulli,Sujit Pal,Francois Chollet

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Solve jigsaw puzzle

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Page Count

699

Publisher

Packt Publishing Ltd

Published Date

ISBN 10

1803245719

ISBN 13

9781803245713

Deep Learning with TensorFlow 2 and Keras

Regression, ConvNets, GANs, RNNs, NLP, and more with TensorFlow 2 and the Keras API, 2nd Edition

By: Antonio Gulli,Amita Kapoor,Sujit Pal

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Deep Learning with TensorFlow 2 and Keras

Regression, ConvNets, GANs, RNNs, NLP, and more with TensorFlow 2 and the Keras API, 2nd Edition

By: Antonio Gulli,Amita Kapoor,Sujit Pal

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647

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Packt Publishing Ltd

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ISBN 10

1838827722

ISBN 13

9781838827724

Book's by Amita Pal

Pattern Recognition

Pattern Recognition

Concise Encyclopaedia of India

Concise Encyclopaedia of India

Cultural Landscapes of India

Cultural Landscapes of India

Deep Learning with TensorFlow 2 and Keras

Deep Learning with TensorFlow 2 and Keras

Essentials of Microbiology for Dental Students - E-Book

Essentials of Microbiology for Dental Students - E-Book

Deep Learning with TensorFlow and Keras

Deep Learning with TensorFlow and Keras

TensorFlow Machine Learning Projects

TensorFlow Machine Learning Projects

Microbiology Practical Manual, 1st Edition-E-book

Microbiology Practical Manual, 1st Edition-E-book

TensorFlow 1.x Deep Learning Cookbook

TensorFlow 1.x Deep Learning Cookbook

Marxism

Marxism

Pattern Recognition

Pattern Recognition

Deep Learning with TensorFlow and Keras

Deep Learning with TensorFlow and Keras

Deep Learning with TensorFlow 2 and Keras

Deep Learning with TensorFlow 2 and Keras

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