Information and Communication Technology: For Education, Healthcare and Rural Development
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The volume aims at providing a comprehensive review of the diverse efforts covering the gap existing between the two main perspectives on the topic of ontologies for multi-agent systems, namely: How ontologies should be modelled and represented in order to be effectively used in agent systems, and on the other hand, what kind of capabilities should be exhibited by an agent in order to make use of ontological knowledge and to perform efficient reasoning with it. The volume collects the most significant papers of the AAMAS 2002 and AAMAS 2003 workshop on ontologies for agent systems, and the EKAW 2002 workshop on ontologies for multi-agent systems.
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Correlation does not imply causation.’ This mantra was invoked by scientists for decades in order to avoid taking positions as to whether one thing caused another, such as smoking and cancer and carbon dioxide and global warming. But today, that taboo is dead. The causal revolution, sparked by world-renowned computer scientist Judea Pearl and his colleagues, has cut through a century of confusion and placed cause and effect on a firm scientific basis. Now, Pearl and Science journalist Dana Mackenzie explain causal thinking to General readers for the first time, showing how it allows us to explore the world that is and the worlds that could have been. It is the essence of human and artificial intelligence. And just as pearl’s discoveries have enabled machines to think better, the book of why explains how we can think better.
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Peeling Design Patterns For Beginners And Interviews presents the subject of Design Patterns in a very easy to understand manner. It can come in handy as a reference material for working professionals, graduate and postgraduate students. Summary Of The Book Peeling Design Patterns For Beginners And Interviews introduces in a simple yet effective manner, the concepts of Software Design Patterns to even those who do not have a prior knowledge of Software Design. This book provides the reader with typical questions that can appear in a job interview. It is also a useful study guide for computer science students. The book is divided into nine chapters. All codes that appear in this book are written in Java. The first three chapters deal with the basics and cover topics related to UML and an introduction to Design Patterns. The next three chapters are about Creational, Structural and Behavioral Patterns. Towards the end of the book is a full glossary for easy retrieval of information, tips, miscellaneous concepts and interview questions related to Design. A reading of Peeling Design Patterns For Beginners and Interviews promises all those working professionals the ability to come up with improvised designs and participate actively in discussions related to Design Patterns at their workplaces. The book is also filled with real-time examples for a reader to fully grasp the concepts pertaining to Software Design Patterns. The book is written in a simple and easy manner with clear explanations. About The Authors Narasimha Karumanchi is an author and the co-founder of careermonk.com. A few of his other books are Data Structures And Algorithms Made Easy In Java, Coding Interview Questions and Data Structures and Algorithms Made Easy. Karumanchi hails from Andhra Pradesh, India. He is a holder of a B.Tech. degree in Computer Science from JNT University and M.Tech. from IIT-Mumbai. His career has spanned stints at Amazon Corporation, IBM Labs, Microsoft and Mentor Graphics. His areas of interest have been Data Structures and Algorithms, which he has also taught in various colleges and training institutes. M. Sreenivasa Rao is an Author, the Director of the School of IT, and the Professor of SIT Computer Science at the Jawaharlal Nehru Technological University, Hyderabad. His articles and papers have been published in leading journals across the world. He holds a B.Tech degree and two M.Tech degrees, as well as a Ph.D. He has nearly 30 years of teaching experience.
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Data Structures And Algorithms Made Easy In Java is a comprehensive and wide-ranging guide on data structures. – Imported Edition Summary Of The Book Data Structures And Algorithms Made Easy In Java is a guide which helps you understand data structures better. Data structures are ways in which data is stored and organised on a computer so as to make it more resourceful. There are different kinds of data structures available for different tasks, with some being highly specific and others used for certain applications. They help in effectively managing large quantities of data with the help of algorithms which, in the fields of mathematics and computer science, is a systematic procedure towards solving any numerical problem. The book covers many topics concerning competitive examinations and includes numerous puzzles and probable interview questions to help the reader prepare better. Each question also comes with multiple solutions of varying complexities so as to enable the reader to deal with a variety of questions. Furthermore, all codes in the book have been written using the Java script. It is a complete preparation guide for likely job aspirants for companies like Oracle, Microsoft, Amazon, Facebook and for people appearing for competitive examinations. Data Structures And Algorithms Made Easy In Java has a comprehensive introduction and various informative chapters such as Linked Lists, Stacks, Queues, Sorting, Searching, Symbol Tables, Dynamic Programming, Complexity Classes and Miscellaneous Concepts. Salient Features of Book All code written in Java Data structure puzzles to improve thinking Enumeration of possible solutions for each problem Covers all topics for competitive exams Covers interview questions on data structures and algorithms Reference Manual for working people Campus Preparation Degree/Masters Course Preparation Big Job Hunters: Microsoft, Google, Amazon, Yahoo, Oracle, Facebook & many more. About the Author Narasimha Karumanchi is the author of many popular books on data structures and algorithms and a software developer. Some of his books are Data Structures and Algorithms Made Easy: 700 Data Structure and Algorithmic Puzzles, Data Structures and Algorithms For GATE: Solutions To All previous GATE Questions Since 1991, Peeling Design Patterns and Coding Interview Questions. Karumanchi was born in Kambhampadu, Guntur, Andhra Pradesh. He graduated with a B.Tech. degree in computer science from JNT University and with an M.Tech. degree in the same discipline from IIT Bombay. He has previously worked with IBM Labs, Hyderabad, Mentor Graphics and Microsoft. He is presently working as a senior software developer at Amazon Corporation, India. He is the founder of CareerMonk and also designs algorithms for Stockmonks.com. Karumanchi has also taught at many training centres and colleges. Narasimha Karumanchi is the Senior Software Developer at Amazon Corporation, India. Most recently he worked for IBM Labs, Hyderabad and prior to that he served for Mentor Graphics and Microsoft, Hyderabad. He received his B-TECH. in Computer Science from JNT University and his M-Tech. in Computer Science from IIT Bombay. He has experience in teaching data structures and algorithms at various training centers and colleges. He was born and bought up in Kambhampadu, Macherla (Palnadu), Guntur, Andhra Pradesh.
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The book provides detailed solutions for data structure and algorithm related questions in previous years GATE Papers. Summary Of The Book Algorithms and data structures are fundamental concepts in computer science, programming and related courses. A good understanding of these concepts are required in the workplace as well as for higher studies. For a person aiming to gain entry into postgraduate courses in IT related fields, this knowledge is of utmost importance. For students who have finished their bachelor degree in computer science, this might not be a problem. They might have a good understanding of these concepts. Still, when appearing for an exam like GATE, they will need to tackle challenging questions on these topics. Data Structures And Algorithms For GATE: Solutions To All Previous Gate Questions Since 1991 helps them by concentrating on the concepts and codes that are directly relevant to competitive exams and interview situations. The book covers theorems and proofs for data structure and algorithm related concepts. It provides different solutions, in varying levels of complexities for the same problems. This will help the students understand many possible solutions to a specific problem. The book concentrates more on problem solving than on the basic theory, for it is assumed that readers at this level understand enough of the theory to tackle various kinds of problems. This book will help readers prepare for competitive exams, for interviews, and even serve as basic reference material for higher studies. Instructors might also find this book useful, as it provides multiple solutions to various problems and discusses the solutions too. Data Structures And Algorithms For GATE: Solutions To All Previous Gate Questions Since 1991 will be especially helpful to GATE aspirants for it contains detailed solutions to questions from previous twenty years of GATE Papers. All the codes in Data Structures And Algorithms For GATE: Solutions To All Previous Gate Questions Since 1991 have been written in C. The book covers data structure topics like linked lists, stacks, queues and trees. It also covers recursions and backtracking. The book discusses various algorithm concepts like searching, sorting and graph algorithms. It goes into string algorithms, hashing techniques and symbol tables. The book also looks into interesting and complex algorithm concepts like dynamic programming, divide and conquer algorithm and greedy algorithms. About Narasimha Karumanchi Narasimha Karumanchi is an experienced software designer and developer. Other books by this author are Peeling Design Patterns: For Beginners And Interviews, Coding Interview Questions, and Data Structure Puzzles: Puzzle Your Mind For Data Structures. He specializes in covering programming and data structure concepts for competitive exams and interviews. Narasimha Karumanchi studied for his B.Tech in computer science at JNT University. He earned his M.Tech from IIT, Bombay. He has worked for Mentor Graphics, Microsoft, and IBM Labs. He also has teaching experience, having taught algorithm and data structures at colleges and training centers. Currently, he is Senior Software Developer at Amazon Corporation.
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Peeling Data Structures and Algorithms:
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“Data Structures And Algorithms Made Easy: Data Structures and Algorithmic Puzzles” is a book that offers solutions to complex data structures and algorithms. There are multiple solutions for each problem and the book is coded in C/C++, it comes handy as an interview and exam guide for computer scientists.
A handy guide of sorts for any computer science professional, Data Structures And Algorithms Made Easy: Data Structures and Algorithmic Puzzles is a solution bank for various complex problems related to data structures and algorithms. It can be used as a reference manual by those readers in the computer science industry. This book serves as guide to prepare for interviews, exams, and campus work. In short, this book offers solutions to various complex data structures and algorithmic problems.
- Recursion and Backtracking
- Linked Lists
- Priority Queue and Heaps
- Disjoint Sets ADT
- Graph Algorithms
- Selection Algorithms [Medians]
- Symbol Tables
- String Algorithms
- Algorithms Design Techniques
- Greedy Algorithms
- Divide and Conquer Algorithms
- Dynamic Programming
- Complexity Classes
- Miscellaneous Concepts
The main objective of writing this book is that every student should be able to acquire necessary skills required to become a programmer. The logic of each and every problem is explained in a simple manner which helps the student to write better programs. This book discusses all concepts of C starting from fundamentals to advanced topics in a lucid manner. It covers hundreds of solved programs which are useful to the students for their examinations. It also covers the interview questions which help the students come up with flying colors in their career.
- All the concepts are discussed in a lucid, easy to understand manner.
- A reader without any basic knowledge in computer s can comfortably follow this book.
- Helps to build logic in the students which becomes stepping stone for programming.
- Interview questions collected from the actual interviews of various Software companies will help the students to be successful in their campus interviews.
- Hundreds of solved programs help the students of Indian Universities do well in their examinations like B.C.A, B.Sc, M.Sc, M.C.A, B.E, B.Tech, M.Tech, etc.
- Works like a handy reference to the Software professionals in their programming.
- Starting at basic level, this book covers advanced topics like Pointers, Data structures, Searching and sorting techniques and Graphics.
Table of Contents:
- 1. Fundamental Concepts in C
2. Data types and operators
3. Control statements in C
6. Characters and strings
7. Storage Classes
9. Structures and Unions
10. File Concepts
11. Command Line Arguments
12. Macros and Enumerations
13. Data Structures in C
14. Searching, Sorting and Merging
15. Graphics and Animation
Apendix – I: List of Programs
Apendix – I :List of Interview Questions
Deep learning doesn’t have to be intimidating. Until recently, this machine-learning method required years of study, but with frameworks such as Keras and Tensorflow, software engineers without a background in machine learning can quickly enter the field. With the recipes in this cookbook, you’ll learn how to solve deep-learning problems for classifying and generating text, images, and music. Each chapter consists of several recipes needed to complete a single project, such as training a music recommending system. Author Douwe Osinga also provides a chapter with half a dozen techniques to help you if you’re stuck. Examples are written in Python with code available on GitHub as a set of Python notebooks. You’ll learn how to: Create applications that will serve real users Use word embeddings to calculate text similarity Build a movie recommender system based on Wikipedia links Learn how AIs see the world by visualizing their internal state Build a model to suggest emojis for pieces of text Reuse pretrained networks to build an inverse image search service Compare how GANs, autoencoders and LSTMs generate icons Detect music styles and index song collections
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AN INTRODUCTION TO MACHINE LEARNING THAT INCLUDES THE FUNDAMENTAL TECHNIQUES, METHODS, AND APPLICATIONS Machine Learning: a Concise Introduction offers a comprehensive introduction to the core concepts, approaches, and applications of machine learning. The author–an expert in the field–presents fundamental ideas, terminology, and techniques for solving applied problems in classification, regression, clustering, density estimation, and dimension reduction. The design principles behind the techniques are emphasized, including the bias-variance trade-off and its influence on the design of ensemble methods. Understanding these principles leads to more flexible and successful applications. Machine Learning: a Concise Introduction also includes methods for optimization, risk estimation, and model selection– essential elements of most applied projects. This important resource: Illustrates many classification methods with a single, running example, highlighting similarities and differences between methods Presents R source code which shows how to apply and interpret many of the techniques covered Includes many thoughtful exercises as an integral part of the text, with an appendix of selected solutions Contains useful information for effectively communicating with clients A volume in the popular Wiley Series in Probability and Statistics, Machine Learning a Concise Introduction offers the practical information needed for an understanding of the methods and application of machine learning. STEVEN W. KNOX holds a Ph.D. in Mathematics from the University of Illinois and an M.S. in Statistics from Carnegie Mellon University. He has over twenty years’ experience in using Machine Learning, Statistics, and Mathematics to solve real-world problems. He currently serves as Technical Director of Mathematics Research and Senior Advocate for Data Science at the National Security Agency.
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