Ignou Data Science Big Data
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Ignou Mca Data Science And Big Data Previous Years Unsolved Papers Mcs 226
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Author : Manish Soni
language : en
Publisher:
Release Date : 2024-11-13
Ignou Mca Data Science And Big Data Previous Years Unsolved Papers Mcs 226 written by Manish Soni and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-13 with Study Aids categories.
The fields of Data Science and Big Data have become cornerstones of modern technology and business, revolutionizing the way organizations operate, make decisions, and drive innovation. As industries across the globe increasingly rely on data to gain insights and maintain competitive advantages, the demand for skilled professionals in Data Science and Big Data has soared. Recognizing this, IGNOU offers a comprehensive course designed to equip students with the theoretical knowledge and practical skills required to excel in these dynamic and rapidly evolving fields. This book, "IGNOU Data Science and Big Data: Previous Years Unsolved Papers," has been meticulously compiled to serve as a vital resource for students pursuing this course. The collection of previous years' unsolved papers included in this book is intended to provide students with a clear understanding of the exam format, the variety of questions posed, and the key topics that have been emphasized in past assessments. These papers are an invaluable tool for students to practice and hone their problem-solving skills, gain familiarity with the types of challenges they may encounter in exams, and identify areas where further study may be needed. By working through these unsolved papers, students are not merely preparing for their exams; they are also deepening their understanding of the core principles and advanced techniques of Data Science and Big Data. Each question in these papers has been designed to test not just knowledge, but the ability to apply concepts to real-world problems, analyse data critically, and derive meaningful conclusions—skills that are essential for any aspiring data scientist or big data professional. This collection also serves to encourage students to think analytically and develop a mindset geared toward innovation and discovery. In the fast-paced world of data, where new tools and methodologies are constantly emerging, the ability to think critically and adapt to new challenges is as important as the foundational knowledge itself. Moreover, these unsolved papers provide an opportunity for students to simulate exam conditions, allowing them to manage their time effectively and develop strategies for tackling difficult questions under pressure. This practice is invaluable in building the confidence needed to approach exams with a calm and focused mindset. We believe that this book will not only be a key element in your exam preparation but also a significant aid in your overall academic and professional journey. By engaging deeply with the material presented here, you will be better equipped to meet the demands of the Data Science and Big Data fields and to contribute meaningfully to the ever-growing landscape of data-driven innovation. Whether you are preparing for your upcoming exams, revising key concepts, or seeking to challenge yourself with complex problems, this collection of unsolved papers will serve as a trusted guide and companion. We encourage you to approach these papers with diligence and curiosity, and we wish you success in your studies and beyond.
Advances In Machine Learning And Big Data Analytics I
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Author : Ashokkumar Patel
language : en
Publisher: Springer Nature
Release Date : 2025-01-31
Advances In Machine Learning And Big Data Analytics I written by Ashokkumar Patel and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-31 with Mathematics categories.
This edited volume on machine learning and big data analytics (Proceedings of ICMLBDA 2023, that was held on May 29-30, 2023 by NERIST and NIT Arunachal Pradesh India) is intended to be used as a reference book for researchers and professionals to share their research and reports of new technologies and applications in Machine Learning and Big Data Analytics like biometric Recognition Systems, medical diagnosis, industries, telecommunications, AI Petri Nets Model-Based Diagnosis, gaming, stock trading, Intelligent Aerospace Systems, robot control, law, remote sensing and scientific discovery agents and multiagent systems; and natural language and Web intelligence. The intent of this book is to provide awareness of algorithms used for machine learning and big data in the advanced Scientific Technologies, provide a correlation of multidisciplinary areas and become a point of great interest for Data Scientists, systems architects, developers, new researchers and graduate level students. This volume provides cutting-edge research from around the globe on this field. Current status, trends, future directions, opportunities, etc. are discussed, making it friendly for beginners and young researchers.
Ignou Mca Third Semester Previous Years Unsolved Papers
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Author : Manish Soni
language : en
Publisher:
Release Date : 2024-11-13
Ignou Mca Third Semester Previous Years Unsolved Papers written by Manish Soni and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-13 with Reference categories.
It is with great pleasure that we present IGNOU MCA Third Semester Previous Years Unsolved Papers, a comprehensive collection of previous years' question papers, meticulously curated to support students pursuing a Master of Computer Applications (MCA) degree from the Indira Gandhi National Open University (IGNOU). This book is designed to serve as a valuable resource for students preparing for their MCA exams, helping them not only to understand the examination pattern but also to enhance their problem-solving skills and self-assessment abilities. The IGNOU MCA program is one of the most reputed distance learning programs in India, and it requires students to possess both theoretical knowledge and practical skills across various subjects related to computer science, software development, and application management. Given the vastness of the syllabus and the technical rigor of the program, students often seek additional support material to solidify their understanding of key concepts and prepare effectively for the exams. This book is intended to fill that gap by providing a comprehensive set of unsolved question papers from previous years. In today’s competitive academic environment, exam preparation is no longer just about understanding the concepts—it’s about mastering the examination pattern, practicing time management, and gaining the confidence to face complex questions with ease. One of the best ways to achieve this is by going through previous years' question papers. This book includes question papers from various subjects covered in the MCA curriculum, including programming languages, algorithms, database management systems, software engineering, data structures, computer networks, and more. By working through these unsolved papers, students can: Understand the Examination Pattern: IGNOU’s question papers have a specific structure, with questions ranging from multiple-choice to short answer and long essay-type questions. By familiarizing themselves with the pattern, students can plan their time effectively during the exam. Identify Important Topics: Previous question papers are an excellent indicator of frequently asked topics. By solving these papers, students can focus on key areas that have a higher probability of appearing in the exams. Enhance Problem-Solving Skills: The unsolved papers encourage students to think critically and apply their theoretical knowledge to practical problems. This process of self-discovery helps in strengthening core concepts and improving analytical skills. Practice Time Management: One of the biggest challenges in any exam is managing time effectively. By solving previous years' papers under timed conditions, students can practice completing the papers within the given time frame, helping them avoid last-minute rushes during the actual exams. Self-Evaluate: After attempting the unsolved papers, students can cross-check their answers with textbooks or online resources. This process of self-evaluation is invaluable in identifying areas of weakness and focusing on them before the exams.
Effective Big Data Management And Opportunities For Implementation
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Author : Singh, Manoj Kumar
language : en
Publisher: IGI Global
Release Date : 2016-06-20
Effective Big Data Management And Opportunities For Implementation written by Singh, Manoj Kumar and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-06-20 with Computers categories.
“Big data” has become a commonly used term to describe large-scale and complex data sets which are difficult to manage and analyze using standard data management methodologies. With applications across sectors and fields of study, the implementation and possible uses of big data are limitless. Effective Big Data Management and Opportunities for Implementation explores emerging research on the ever-growing field of big data and facilitates further knowledge development on methods for handling and interpreting large data sets. Providing multi-disciplinary perspectives fueled by international research, this publication is designed for use by data analysts, IT professionals, researchers, and graduate-level students interested in learning about the latest trends and concepts in big data.
Big Data Analytics In Cognitive Social Media And Literary Texts
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Author : Sanjiv Sharma
language : en
Publisher: Springer Nature
Release Date : 2021-10-10
Big Data Analytics In Cognitive Social Media And Literary Texts written by Sanjiv Sharma and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-10 with Language Arts & Disciplines categories.
This book provides a comprehensive overview of the theory and praxis of Big Data Analytics and how these are used to extract cognition-related information from social media and literary texts. It presents analytics that transcends the borders of discipline-specific academic research and focuses on knowledge extraction, prediction, and decision-making in the context of individual, social, and national development. The content is divided into three main sections: the first of which discusses various approaches associated with Big Data Analytics, while the second addresses the security and privacy of big data in social media, and the last focuses on the literary text as the literary data in Big Data Analytics. Sharing valuable insights into the etiology behind human cognition and its reflection in social media and literary texts, the book benefits all those interested in analytics that can be applied to literature, history, philosophy, linguistics, literary theory, media & communication studies and computational/digital humanities.
Aiot And Big Data Analytics For Smart Healthcare Applications
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Author : Shreyas Suresh Rao, Steven Lawrence Fernandes, Chandra Singh, Rathishchandra R. Gatti, Harisha A., Rohanchandra R. Gatty
language : en
Publisher: Bentham Science Publishers
Release Date : 2023-12-26
Aiot And Big Data Analytics For Smart Healthcare Applications written by Shreyas Suresh Rao, Steven Lawrence Fernandes, Chandra Singh, Rathishchandra R. Gatti, Harisha A., Rohanchandra R. Gatty and has been published by Bentham Science Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-26 with Computers categories.
AIoT (Artificial Intelligence of Things) and Big Data Analytics are catalyzing a healthcare revolution. This book is an accessible volume that summarizes the information available. In this book, researchers explore how AIoT and Big Data can seamlessly integrate into healthcare, enhancing medical services and devices while adhering to established protocols. The book demonstrates the crucial role of these technologies during healthcare crises like the COVID-19 pandemic. It presents novel solutions and computational techniques powered by AIoT, Machine Learning, and Deep Learning, providing a new frontier in healthcare problem-solving. Key Features: Real-Life Illustrations: Real-world examples showcase AIoT and Big Data in action, highlighting their impact in healthcare. Comprehensive Exploration: The book offers a thorough examination of AIoT, Big Data, and their harmonious synergy within the healthcare landscape. Visual Aids: Complex concepts become approachable through diagrams, flowcharts, and infographics, making technical processes and system designs more digestible. Ethical Insights: Delving into the ethical dimensions of AIoT and Big Data, it addresses concerns like data bias, patient consent, and transparency in healthcare. Forward-Looking Discourse: The book engages with emerging trends, potential innovations, and the future direction of AIoT and Big Data, making it a compass for healthcare transformation. Researchers, whether from academia, industry, or research and development organizations, interested in AIoT, Big Data, artificial intelligence, and healthcare optimization, will find this book informative. It also serves as an update for tech enthusiasts who want to explore the future of healthcare powered by AI and data.
Ignou Blis Solved Assignment 2024 25 In English
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Author : Navneet Verma
language : en
Publisher: Digicraft
Release Date :
Ignou Blis Solved Assignment 2024 25 In English written by Navneet Verma and has been published by Digicraft this book supported file pdf, txt, epub, kindle and other format this book has been release on with Juvenile Nonfiction categories.
IGNOU BLIS Solved Assignment 2024-25 (English) Prepare for your IGNOU BLIS (Bachelor of Library and Information Science) exams with our Solved Assignment for the 2024-25 academic session! This comprehensive set of solved assignments covers all the subjects and topics included in the BLIS program, designed to help you score high and complete your assignments with ease. Why Choose Our Solved Assignment? Complete Coverage: Our assignments are based on the official IGNOU syllabus, ensuring you cover all topics in detail. Accurate and Well-Researched Solutions: Each assignment is carefully solved by experts to provide you with the most accurate and up-to-date answers. Time-Saving: With ready-made solutions, you save valuable time and focus on your exam preparation. Easy to Understand: The solutions are written in clear, concise English, making complex topics easy to understand. Instant Download: Once you make your purchase, you’ll get immediate access to download the solved assignments in PDF format. Subjects Covered: BLI 221-229 Features: High-Quality Content: Professionally crafted answers to ensure your assignments are top-notch. Perfect for Submission: These solved assignments are ready for direct submission to IGNOU. Affordable: Get expert solutions at an affordable price, helping you succeed without breaking the bank. How to Get It: Simply make a purchase through our website/Google Books/Amazon Kindle. Download the solved assignment instantly in PDF format. Submit your completed assignments to IGNOU for evaluation. Note: We recommend you thoroughly review and personalize the answers before submission
Machine Learning And Data Analytics For Predicting Managing And Monitoring Disease
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Author : Roy, Manikant
language : en
Publisher: IGI Global
Release Date : 2021-06-25
Machine Learning And Data Analytics For Predicting Managing And Monitoring Disease written by Roy, Manikant and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-25 with Computers categories.
Data analytics is proving to be an ally for epidemiologists as they join forces with data scientists to address the scale of crises. Analytics examined from many sources can derive insights and be used to study and fight global outbreaks. Pandemic analytics is a modern way to combat a problem as old as humanity itself: the proliferation of disease. Machine Learning and Data Analytics for Predicting, Managing, and Monitoring Disease explores different types of data and discusses how to prepare data for analysis, perform simple statistical analyses, create meaningful data visualizations, predict future trends from data, and more by applying cutting edge technology such as machine learning and data analytics in the wake of the COVID-19 pandemic. Covering a range of topics such as mental health analytics during COVID-19, data analysis and machine learning using Python, and statistical model development and deployment, it is ideal for researchers, academicians, data scientists, technologists, data analysts, diagnosticians, healthcare professionals, computer scientists, and students.
Big Data Analytics In The Insurance Market
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Author : Kiran Sood
language : en
Publisher: Emerald Group Publishing
Release Date : 2022-07-18
Big Data Analytics In The Insurance Market written by Kiran Sood and has been published by Emerald Group Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-18 with Business & Economics categories.
Big Data Analytics in the Insurance Market is an industry-specific guide to creating operational effectiveness, managing risk, improving financials, and retaining customers. A must for people seeking to broaden their knowledge of big data concepts and their real-world applications, particularly in the field of insurance.
Learn R For Applied Statistics
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Author : Eric Goh Ming Hui
language : en
Publisher: Apress
Release Date : 2018-11-30
Learn R For Applied Statistics written by Eric Goh Ming Hui and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-30 with Computers categories.
Gain the R programming language fundamentals for doing the applied statistics useful for data exploration and analysis in data science and data mining. This book covers topics ranging from R syntax basics, descriptive statistics, and data visualizations to inferential statistics and regressions. After learning R’s syntax, you will work through data visualizations such as histograms and boxplot charting, descriptive statistics, and inferential statistics such as t-test, chi-square test, ANOVA, non-parametric test, and linear regressions. Learn R for Applied Statistics is a timely skills-migration book that equips you with the R programming fundamentals and introduces you to applied statistics for data explorations. What You Will Learn Discover R, statistics, data science, data mining, and big data Master the fundamentals of R programming, including variables and arithmetic, vectors, lists, data frames, conditional statements, loops, and functions Work with descriptive statistics Create data visualizations, including bar charts, line charts, scatter plots, boxplots, histograms, and scatterplots Use inferential statistics including t-tests, chi-square tests, ANOVA, non-parametric tests, linear regressions, and multiple linear regressions Who This Book Is For Those who are interested in data science, in particular data exploration using applied statistics, and the use of R programming for data visualizations.