Algorithmic Reading Comprehension

DOWNLOAD
Download Algorithmic Reading Comprehension PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Algorithmic Reading Comprehension book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Algorithmic Reading Comprehension
DOWNLOAD
Author : Rahul Anand
language : en
Publisher: Educreation Publishing
Release Date : 2018-10-10
Algorithmic Reading Comprehension written by Rahul Anand and has been published by Educreation Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-10 with Education categories.
Reading comprehension solving is a skill. It is different from literature in the sense that it is independent of interpretation. There is no subjectivity in RC questions. The art of solving can be learnt by mastering the topic at three levels – The ability to read, to eliminate options and to build mistake patterns to learn from them. These three levels lie at the core of "Algorithmic Reading Comprehension" – an approach to build expertise in RC solving. This approach was created by my team and me over the past 6 years of training thousands of students for the Reading comprehension section for CAT-GMAT and other aptitude-based entrance examinations. The book deals with two major aspects of reading, "Central Idea" and "Contextual Word Learning". It moves on to discuss the meaning of different question types asked across exams and provides elimination frameworks to tackle tricky options. Finally, students get many passages arranged in levels and then in a practice chapter to practice and to learn from. Welcome to the world of flawless RC learning!
Machine Reading Comprehension
DOWNLOAD
Author : Chenguang Zhu
language : en
Publisher: Elsevier
Release Date : 2021-03-20
Machine Reading Comprehension written by Chenguang Zhu and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-20 with Computers categories.
Machine reading comprehension (MRC) is a cutting-edge technology in natural language processing (NLP). MRC has recently advanced significantly, surpassing human parity in several public datasets. It has also been widely deployed by industry in search engine and quality assurance systems. Machine Reading Comprehension: Algorithms and Practice performs a deep-dive into MRC, offering a resource on the complex tasks this technology involves. The title presents the fundamentals of NLP and deep learning, before introducing the task, models, and applications of MRC. This volume gives theoretical treatment to solutions and gives detailed analysis of code, and considers applications in real-world industry. The book includes basic concepts, tasks, datasets, NLP tools, deep learning models and architecture, and insight from hands-on experience. In addition, the title presents the latest advances from the past two years of research. Structured into three sections and eight chapters, this book presents the basis of MRC; MRC models; and hands-on issues in application. This book offers a comprehensive solution for researchers in industry and academia who are looking to understand and deploy machine reading comprehension within natural language processing. - Presents the first comprehensive resource on machine reading comprehension (MRC) - Performs a deep-dive into MRC, from fundamentals to latest developments - Offers the latest thinking and research in the field of MRC, including the BERT model - Provides theoretical discussion, code analysis, and real-world applications of MRC - Gives insight from research which has led to surpassing human parity in MRC
Concept Parsing Algorithms Cpa For Textual Analysis And Discovery Emerging Research And Opportunities
DOWNLOAD
Author : Shafrir, Uri
language : en
Publisher: IGI Global
Release Date : 2017-07-13
Concept Parsing Algorithms Cpa For Textual Analysis And Discovery Emerging Research And Opportunities written by Shafrir, Uri and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-13 with Computers categories.
Text analysis tools aid in extracting meaning from digital content. As digital text becomes more and more complex, new techniques are needed to understand conceptual structure. Concept Parsing Algorithms (CPA) for Textual Analysis and Discovery: Emerging Research and Opportunities provides an innovative perspective on the application of algorithmic tools to study unstructured digital content. Highlighting pertinent topics such as semantic tools, semiotic systems, and pattern detection, this book is ideally designed for researchers, academics, students, professionals, and practitioners interested in developing a better understanding of digital text analysis.
Algorithmic Intimacy
DOWNLOAD
Author : Anthony Elliott
language : en
Publisher: John Wiley & Sons
Release Date : 2022-10-11
Algorithmic Intimacy written by Anthony Elliott and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-11 with Social Science categories.
Artificial intelligence not only powers our cars, hospitals and courtrooms: predictive algorithms are becoming deeply lodged inside us too. Machine intelligence is learning our private preferences and discreetly shaping our personal behaviour, telling us how to live, who to befriend and who to date. In Algorithmic Intimacy, Anthony Elliott examines the power of predictive algorithms in reshaping personal relationships today. From Facebook friends and therapy chatbots to dating apps and quantified sex lives, Elliott explores how machine intelligence is working within us, amplifying our desires and steering our personal preferences. He argues that intimate relationships today are threatened not by the digital revolution as such, but by the orientation of various life strategies unthinkingly aligned with automated machine intelligence. Our reliance on algorithmic recommendations, he suggests, reflects a growing emergency in personal agency and human bonds. We need alternatives, innovation and experimentation for the interpersonal, intimate effort of ongoing translation back and forth between the discourses of human and machine intelligence. Accessible and compelling, this book sheds fresh light on the impact of artificial intelligence on the most intimate aspects of our lives. It will appeal to students in the social sciences and humanities and to a wide range of general readers.
The Algorithmic Classroom Reimagining Education In The Age Of Intelligent Systems
DOWNLOAD
Author : KHRITISH SWARGIARY
language : en
Publisher: ERA,US
Release Date : 2025-05-07
The Algorithmic Classroom Reimagining Education In The Age Of Intelligent Systems written by KHRITISH SWARGIARY and has been published by ERA,US this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-07 with Computers categories.
The Algorithmic Classroom: Reimagining Education in the Age of Intelligent Systems
Reinforcement Learning Foundations Algorithms And Applications
DOWNLOAD
Author : Dr. Darío Salguero García
language : en
Publisher: Xoffencerpublication
Release Date : 2023-09-18
Reinforcement Learning Foundations Algorithms And Applications written by Dr. Darío Salguero García and has been published by Xoffencerpublication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-18 with Computers categories.
Reinforcement learning, sometimes known as RL, is a catchall word that refers to both a learning problem and a subfield in machine learning. In the context of a problem involving learning, this refers to the process of determining how to guide a computer toward an arbitrary numerical objective. The process of reinforcement learning may be seen in its usual application in the controller is provided with both the present state of the system under their control as well as the reward earned from the most recent transition. After that, the system will calculate an answer and then provide it to you. Because of this, the system goes through a state transition, and the process starts all over again. Figuring out how to have the most possible impact on the system in order to get the greatest possible advantage from it is the task at hand here. The gathering of data and the measurement of performance are two areas in which the learning obstacles are distinct. In this context, we make the assumption that the target system is, by its very nature, unpredictable. In addition, we make the assumption that the measures of state that are now accessible are detailed enough so that the controller does not need to speculate on how to get state information. The Markovian decision processes, often known as MDPs, provide a helpful framework for modeling issues that include these characteristics. MDPs are often "solved" via the use of dynamic programming, which, in practice, does nothing more than recast the initial problem as one involving the selection of an acceptable value function. Dynamic programming, on the other hand, is impractical in all but the most elementary of situations, namely those in which the MDP has a limited number of states and actions. The RL algorithms that we give here may be seen as a method that can be utilized to turn unfeasible dynamic programming into usable algorithms that can be used to real-world applications on a huge scale. The reason why RL algorithms are able to do this task is due to two key assumptions. The fundamental idea is to illustrate the dynamics of the control issue in a more concise way by utilizing samples. This is crucial for two reasons, which are as follows: To begin, it makes it easier to handle learning circumstances that include dynamics that are unknown.
Algorithms In Advanced Artificial Intelligence
DOWNLOAD
Author : R. N. V. Jagan Mohan
language : en
Publisher: CRC Press
Release Date : 2025-05-23
Algorithms In Advanced Artificial Intelligence written by R. N. V. Jagan Mohan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-23 with Computers categories.
Algorithms in Advanced Artificial Intelligence is a collection of papers on emerging issues, challenges, and new methods in Artificial Intelligence, Machine Learning, Deep Learning, Cloud Computing, Federated Learning, Internet of Things, and Blockchain technology. It addresses the growing attention to advanced technologies due to their ability to provide “paranormal solutions” to problems associated with classical Artificial Intelligence frameworks. AI is used in various subfields, including learning, perception, and financial decisions. It uses four strategies: Thinking Humanly, Thinking Rationally, Acting Humanly, and Acting Rationally. The authors address various issues in ICT, including Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Big Data Analytics, Vision, Internet of Things, Security and Privacy aspects in AI, and Blockchain and Digital Twin Integrated Applications in AI.
Machine Learning Mastery Algorithms Applications And Insights
DOWNLOAD
Author : Dr. Pramod Kumar
language : en
Publisher: Xoffencerpublication
Release Date : 2023-08-14
Machine Learning Mastery Algorithms Applications And Insights written by Dr. Pramod Kumar and has been published by Xoffencerpublication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-14 with Computers categories.
Machine learning is an area of artificial intelligence (AI) that focuses on the development of algorithms and models that allow computers to learn and make predictions or judgments without being explicitly programmed. This is accomplished by teaching the computer to learn from its own experiences. The creation and development of computer systems that are able to automatically analyze and understand complicated data in order to enhance their performance over time is the focus of this field. The foundation of machine learning is the construction of mathematical models that are capable of gaining knowledge from data. These models are educated using a collection of instances that have been labeled. This collection of examples is referred to as the training data, and it includes input features as well as output labels or goal values. Adjusting the model's internal parameters or weights in accordance with the patterns and relationships discovered in the data is what the training process entails. This is done with the intention of achieving a gap that is as narrow as possible between the anticipated outputs and the actual values. Reinforcement learning is a paradigm that entails an agent interacting with an environment and learning to make a series of choices or actions in order to maximize a cumulative reward. This paradigm was developed by Edward de Bono. The agent is provided with feedback in the form of incentives or penalties according to its actions, which teaches it the optimum behavior via the process of trial and error. The methodologies of machine learning are becoming more prevalent in a broad variety of fields and applications. Image and audio recognition, natural language processing, recommendation systems, fraud detection, autonomous cars, and medical diagnostics are just few of the numerous applications that may benefit from AI. Programming languages such as Python and R, in addition to libraries and frameworks such as scikit-learn, TensorFlow, and PyTorch, are often used when it comes to the implementation of machine learning algorithms. These tools offer a comprehensive array of functions and utilities for the preparation of data, as well as for the training, assessment, and deployment of models. Learning via machines is an active topic that is developing at a quick pace because to continuing research and technological breakthroughs. The potential for employing machine learning to tackle difficult issues and promote innovation is continuing to develop as more data becomes accessible and as computer power grows.
Introduction To Algorithms Third Edition
DOWNLOAD
Author : Thomas H. Cormen
language : en
Publisher: MIT Press
Release Date : 2009-07-31
Introduction To Algorithms Third Edition written by Thomas H. Cormen and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-07-31 with Computers categories.
The latest edition of the essential text and professional reference, with substantial new material on such topics as vEB trees, multithreaded algorithms, dynamic programming, and edge-based flow. Some books on algorithms are rigorous but incomplete; others cover masses of material but lack rigor. Introduction to Algorithms uniquely combines rigor and comprehensiveness. The book covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers. Each chapter is relatively self-contained and can be used as a unit of study. The algorithms are described in English and in a pseudocode designed to be readable by anyone who has done a little programming. The explanations have been kept elementary without sacrificing depth of coverage or mathematical rigor. The first edition became a widely used text in universities worldwide as well as the standard reference for professionals. The second edition featured new chapters on the role of algorithms, probabilistic analysis and randomized algorithms, and linear programming. The third edition has been revised and updated throughout. It includes two completely new chapters, on van Emde Boas trees and multithreaded algorithms, substantial additions to the chapter on recurrence (now called “Divide-and-Conquer”), and an appendix on matrices. It features improved treatment of dynamic programming and greedy algorithms and a new notion of edge-based flow in the material on flow networks. Many exercises and problems have been added for this edition. The international paperback edition is no longer available; the hardcover is available worldwide.
Algorithms
DOWNLOAD
Author : B. A. Hoena
language : en
Publisher: Capstone
Release Date : 2018
Algorithms written by B. A. Hoena and has been published by Capstone this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with Computers categories.
Do you have a problem? Maybe you can use an algorithm to fix it! Learn about the codes all around us in Algorithms: Solve a Problem! Sing along as you learn to Code It!