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Pearson is proud to present the 18th edition of its best-selling title General Knowledge Manual 2020. The book is specifically designed to help Civil Services aspirants to master the General Knowledge section, which is also a key part in many other competitive examinations. The book presents the widest span of topics in a very crisp format for easy understanding and remembrance. Features: -Facts-based approach with features, like Quick Facts, Key Terms, and Concept Links to enable faster learning -Includes Jammu and Kashmir Reorganization Bill, 2019; and making of Two new Union Territories – Jammu and Kashmir and Ladakh -Includes the recent data based on Economic Survey (2018-19) and Union Budget 2019-2020 -Discusses recent developments across Politics, Economy and Indian Constitution -Current Affairs section comes with all recent updates on National and International Affairs, Indian Economy, Sports, Awards and Honours across the world -4000+ Practice Questions arranged topic-wise -1400+ Previous Years’ Questions from Key Examinations, like UPSC, State PSC, Banking, Railways, NDA, CDS and other vacancy-based examinations are included online Table of Contents: Section A: Chapter 1.Physical Geography Chapter 2.World Geography Chapter 3. International Organizations Chapter 4. General Knowledge Section B: Chapter 1. Physics Chapter 2. Chemistry Chapter 3. General Biology(Botany and Zoology) Chapter 4. Human Body Chapter 5. Ecosystem and Biosphere Section C: INDIA Chapter 1. History of India and Freedom Struggle Chapter 2. Constitution of India Chapter 3. Population of India Chapter 4. National Awards, Cultureand Literature Chapter 5. Geography of India Chapter 6. Indian Economy Chapter 7. Communication andTransport Systems Chapter 8. Defense and Security Chapter 9. Science and Technology Chapter 10. National Insignia and Other Facts Section D: Current Affairs
Structured and developed for both class room use and self learning, this updated edition is a must buy for aspirants who are preparing for various competitive examinations. The questions have now been segregated by topic and new questions from 'Previous Years' Question Papers' of key examinations have been added for effective preparation. The topics are covered in a thorough fashion with presentation of facts and recent updates spread across Politics, Economy, Science & Technology and National & International Affairs. The book is divided into four Parts 'The World', Science, India and Current Affairs. As an additional feature a 32 page multicolor section containing maps of the world, India and its various physical, geographical and political make up is included along with the book.
This book has been a best seller for more than a decade, currently in its 13th edition it is thoroughly updated and revised with current trend in competitive examinations across various domains. The contents are broadly divided into four sections World, Science, India and Current affairs. Each chapter contains more than 100 MCQs with answer keys. A key feature of this book is the 30 page colorful maps, provided with fact files from authentic sources. The maps also include some added information on geography, population, and economy of the entire continent. Designed and developed for both classroom use and self learning, this updated edition is a must-buy for the aspirants who are planning to crack various competitive examinations.
Structured and developed for both class room use and self learning, this updated edition is a must buy for aspirants who are preparing for various competitive examinations. The questions have now been segregated by topic and new questions from 'Previous Years' Question Papers' of key examinations have been added for effective preparation.
The Book of R is a comprehensive, beginner-friendly guide to R, the world’s most popular programming language for statistical analysis. Even if you have no programming experience and little more than a grounding in the basics of mathematics, you’ll find everything you need to begin using R effectively for statistical analysis. You’ll start with the basics, like how to handle data and write simple programs, before moving on to more advanced topics, like producing statistical summaries of your data and performing statistical tests and modeling. You’ll even learn how to create impressive data visualizations with R’s basic graphics tools and contributed packages, like ggplot2 and ggvis, as well as interactive 3D visualizations using the rgl package. Dozens of hands-on exercises (with downloadable solutions) take you from theory to practice, as you learn: –The fundamentals of programming in R, including how to write data frames, create functions, and use variables, statements, and loops –Statistical concepts like exploratory data analysis, probabilities, hypothesis tests, and regression modeling, and how to execute them in R –How to access R’s thousands of functions, libraries, and data sets –How to draw valid and useful conclusions from your data –How to create publication-quality graphics of your results Combining detailed explanations with real-world examples and exercises, this book will provide you with a solid understanding of both statistics and the depth of R’s functionality. Make The Book of R your doorway into the growing world of data analysis.
This book describes cloud computing as a service that is "highly scalable" and operates in "a resilient environment". The authors emphasize architectural layers and models - but also business and security factors.
For undergraduate or graduate courses that include planning, conducting, and evaluating research. A do-it-yourself, understand-it-yourself manual designed to help students understand the fundamental structure of research and the methodical process that leads to valid, reliable results. Written in uncommonly engaging and elegant prose, this text guides the reader, step-by-step, from the selection of a problem, through the process of conducting authentic research, to the preparation of a completed report, with practical suggestions based on a solid theoretical framework and sound pedagogy. Suitable as the core text in any introductory research course or even for self-instruction, this text will show students two things: 1) that quality research demands planning and design; and, 2) how their own research projects can be executed effectively and professionally.
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 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 concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally 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 topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, 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, 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, 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.