Data Distribution

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Introduction to Data Science

Author : Rafael A. Irizarry
Publisher : CRC Press
ISBN 13 : 1000708039
Total Pages : 836 pages
Book Rating : 4.0/5 (7 download)

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Book Synopsis Introduction to Data Science by : Rafael A. Irizarry

Download or read book Introduction to Data Science written by Rafael A. Irizarry and published by CRC Press. This book was released on 2019-11-20 with total page 836 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to Data Science: Data Analysis and Prediction Algorithms with R introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical inference, linear regression, and machine learning. It also helps you develop skills such as R programming, data wrangling, data visualization, predictive algorithm building, file organization with UNIX/Linux shell, version control with Git and GitHub, and reproducible document preparation. This book is a textbook for a first course in data science. No previous knowledge of R is necessary, although some experience with programming may be helpful. The book is divided into six parts: R, data visualization, statistics with R, data wrangling, machine learning, and productivity tools. Each part has several chapters meant to be presented as one lecture. The author uses motivating case studies that realistically mimic a data scientist’s experience. He starts by asking specific questions and answers these through data analysis so concepts are learned as a means to answering the questions. Examples of the case studies included are: US murder rates by state, self-reported student heights, trends in world health and economics, the impact of vaccines on infectious disease rates, the financial crisis of 2007-2008, election forecasting, building a baseball team, image processing of hand-written digits, and movie recommendation systems. The statistical concepts used to answer the case study questions are only briefly introduced, so complementing with a probability and statistics textbook is highly recommended for in-depth understanding of these concepts. If you read and understand the chapters and complete the exercises, you will be prepared to learn the more advanced concepts and skills needed to become an expert.

Data Distribution

Author : Richard Wiliiams
Publisher : Routledge
ISBN 13 : 042987328X
Total Pages : 168 pages
Book Rating : 4.4/5 (298 download)

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Book Synopsis Data Distribution by : Richard Wiliiams

Download or read book Data Distribution written by Richard Wiliiams and published by Routledge. This book was released on 2018-12-17 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: Published in 1992. Business information has evolved from typewriter/card index (decentralized) through the era of DP Department and mainframe (centralized) to present mix with PCs and networks (distributed). This book demonstrates how data distribution can function in the best interests of organizations, through a managed environment. It looks at what is needed from the systems professionals to support current methods; reporting actual experience, defining techniques, and examining the opportunities and challenges.

China Standard: GB/T 34514-2017 Requirements of remote sensing data distribution and user service for land observation satellite

Author : www.1clicktong.com
Publisher : Risk Management 1 Click Tong
ISBN 13 :
Total Pages : 16 pages
Book Rating : 4./5 ( download)

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Book Synopsis China Standard: GB/T 34514-2017 Requirements of remote sensing data distribution and user service for land observation satellite by : www.1clicktong.com

Download or read book China Standard: GB/T 34514-2017 Requirements of remote sensing data distribution and user service for land observation satellite written by www.1clicktong.com and published by Risk Management 1 Click Tong. This book was released on 2019-07-29 with total page 16 pages. Available in PDF, EPUB and Kindle. Book excerpt: This standard specifies the distribution requirements, service requirements, service procedures, user management requirements and other related technical support and technical services of terrestrial observation satellite remote sensing data. This standard is applicable to the remote sensing data distribution and user service standardization management of terrestrial observation satellites (hereinafter referred to as satellites) in China. Other remote sensing satellite data product distribution and user services can also refer to this standard.

Introductory Business Statistics 2e

Author : Alexander Holmes
Publisher :
ISBN 13 :
Total Pages : 1801 pages
Book Rating : 4./5 ( download)

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Book Synopsis Introductory Business Statistics 2e by : Alexander Holmes

Download or read book Introductory Business Statistics 2e written by Alexander Holmes and published by . This book was released on 2023-12-13 with total page 1801 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introductory Business Statistics 2e aligns with the topics and objectives of the typical one-semester statistics course for business, economics, and related majors. The text provides detailed and supportive explanations and extensive step-by-step walkthroughs. The author places a significant emphasis on the development and practical application of formulas so that students have a deeper understanding of their interpretation and application of data. Problems and exercises are largely centered on business topics, though other applications are provided in order to increase relevance and showcase the critical role of statistics in a number of fields and real-world contexts. The second edition retains the organization of the original text. Based on extensive feedback from adopters and students, the revision focused on improving currency and relevance, particularly in examples and problems. This is an adaptation of Introductory Business Statistics 2e by OpenStax. You can access the textbook as pdf for free at openstax.org. Minor editorial changes were made to ensure a better ebook reading experience. Textbook content produced by OpenStax is licensed under a Creative Commons Attribution 4.0 International License.

Statistics For Dummies

Author : Deborah J. Rumsey
Publisher : John Wiley & Sons
ISBN 13 : 1119293529
Total Pages : 423 pages
Book Rating : 4.1/5 (192 download)

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Book Synopsis Statistics For Dummies by : Deborah J. Rumsey

Download or read book Statistics For Dummies written by Deborah J. Rumsey and published by John Wiley & Sons. This book was released on 2016-06-07 with total page 423 pages. Available in PDF, EPUB and Kindle. Book excerpt: The fun and easy way to get down to business with statistics Stymied by statistics? No fear? this friendly guide offers clear, practical explanations of statistical ideas, techniques, formulas, and calculations, with lots of examples that show you how these concepts apply to your everyday life. Statistics For Dummies shows you how to interpret and critique graphs and charts, determine the odds with probability, guesstimate with confidence using confidence intervals, set up and carry out a hypothesis test, compute statistical formulas, and more. Tracks to a typical first semester statistics course Updated examples resonate with today's students Explanations mirror teaching methods and classroom protocol Packed with practical advice and real-world problems, Statistics For Dummies gives you everything you need to analyze and interpret data for improved classroom or on-the-job performance.

Statistics

Author : David C. LeBlanc
Publisher : Jones & Bartlett Learning
ISBN 13 : 9780763746995
Total Pages : 404 pages
Book Rating : 4.7/5 (469 download)

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Book Synopsis Statistics by : David C. LeBlanc

Download or read book Statistics written by David C. LeBlanc and published by Jones & Bartlett Learning. This book was released on 2004 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: Designed for students majoring in the life, health, and natural sciences, Statistics: Concepts and Applications for Science is a text and workbook package that introduces statistics with an important emphasis on the real-world applications of statistical reasoning and procedures. Through intensive exposure to the core concepts of statistics in the context of science, students acquire the skills and understanding they need to formulate valid research designs, implement statistical analysis, interpret data, and explain their results.

Third Generation Distributed Computing Environments

Author : Amjad Umar
Publisher : nge solutions, inc
ISBN 13 : 9780975918210
Total Pages : 788 pages
Book Rating : 4.9/5 (182 download)

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Book Synopsis Third Generation Distributed Computing Environments by : Amjad Umar

Download or read book Third Generation Distributed Computing Environments written by Amjad Umar and published by nge solutions, inc. This book was released on 2004 with total page 788 pages. Available in PDF, EPUB and Kindle. Book excerpt: Umar provides a collection of powerful services to support the e-business andm-business initiatives of today and tomorrow. (Computer Books)

Data-Driven Business Decisions

Author : Chris J. Lloyd
Publisher : John Wiley & Sons
ISBN 13 : 0470619600
Total Pages : 512 pages
Book Rating : 4.4/5 (76 download)

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Book Synopsis Data-Driven Business Decisions by : Chris J. Lloyd

Download or read book Data-Driven Business Decisions written by Chris J. Lloyd and published by John Wiley & Sons. This book was released on 2011-10-25 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: A hands-on guide to the use of quantitative methods and software for making successful business decisions The appropriate use of quantitative methods lies at the core of successful decisions made by managers, researchers, and students in the field of business. Providing a framework for the development of sound judgment and the ability to utilize quantitative and qualitative approaches, Data Driven Business Decisions introduces readers to the important role that data plays in understanding business outcomes, addressing four general areas that managers need to know about: data handling and Microsoft Excel, uncertainty, the relationship between inputs and outputs, and complex decisions with trade-offs and uncertainty. Grounded in the author's own classroom approach to business statistics, the book reveals how to use data to understand the drivers of business outcomes, which in turn allows for data-driven business decisions. A basic, non-mathematical foundation in statistics is provided, outlining for readers the tools needed to link data with business decisions; account for uncertainty in the actions of others and in patterns revealed by data; handle data in Excel; translate their analysis into simple business terms; and present results in simple tables and charts. The author discusses key data analytic frameworks, such as decision trees and multiple regression, and also explores additional topics, including: Use of the Excel® functions Solver and Goal Seek Partial correlation and auto-correlation Interactions and proportional variation in regression models Seasonal adjustment and what it reveals Basic portfolio theory as an introduction to correlations Chapters are introduced with case studies that integrate simple ideas into the larger business context, and are followed by further details, raw data, and motivating insights. Algebraic notation is used only when necessary, and throughout the book, the author utilizes real-world examples from diverse areas such as market surveys, finance, economics, and business ethics. Excel® add-ins StatproGo and TreePlan are showcased to demonstrate execution of the techniques, and a related website features extensive programming instructions as well as insights, data sets, and solutions to problems included in the material. Data Driven Business Decisions is an excellent book for MBA quantitative analysis courses or undergraduate general statistics courses. It also serves as a valuable reference for practicing MBAs and practitioners in the fields of statistics, business, and finance.

Analysis of Neural Data

Author : Robert E. Kass
Publisher : Springer
ISBN 13 : 1461496020
Total Pages : 663 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Analysis of Neural Data by : Robert E. Kass

Download or read book Analysis of Neural Data written by Robert E. Kass and published by Springer. This book was released on 2014-07-08 with total page 663 pages. Available in PDF, EPUB and Kindle. Book excerpt: Continual improvements in data collection and processing have had a huge impact on brain research, producing data sets that are often large and complicated. By emphasizing a few fundamental principles, and a handful of ubiquitous techniques, Analysis of Neural Data provides a unified treatment of analytical methods that have become essential for contemporary researchers. Throughout the book ideas are illustrated with more than 100 examples drawn from the literature, ranging from electrophysiology, to neuroimaging, to behavior. By demonstrating the commonality among various statistical approaches the authors provide the crucial tools for gaining knowledge from diverse types of data. Aimed at experimentalists with only high-school level mathematics, as well as computationally-oriented neuroscientists who have limited familiarity with statistics, Analysis of Neural Data serves as both a self-contained introduction and a reference work.

Data Representations, Transformations, and Statistics for Visual Reasoning

Author : Ross Maciejewski
Publisher : Morgan & Claypool Publishers
ISBN 13 : 1608456250
Total Pages : 88 pages
Book Rating : 4.6/5 (84 download)

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Book Synopsis Data Representations, Transformations, and Statistics for Visual Reasoning by : Ross Maciejewski

Download or read book Data Representations, Transformations, and Statistics for Visual Reasoning written by Ross Maciejewski and published by Morgan & Claypool Publishers. This book was released on 2011 with total page 88 pages. Available in PDF, EPUB and Kindle. Book excerpt: Analytical reasoning techniques are methods by which users explore their data to obtain insight and knowledge that can directly support situational awareness and decision making. Recently, the analytical reasoning process has been augmented through the use of interactive visual representations and tools which utilize cognitive, design and perceptual principles. These tools are commonly referred to as visual analytics tools, and the underlying methods and principles have roots in a variety of disciplines. This chapter provides an introduction to young researchers as an overview of common visual representations and statistical analysis methods utilized in a variety of visual analytics systems. The application and design of visualization and analytical algorithms are subject to design decisions, parameter choices, and many conflicting requirements. As such, this chapter attempts to provide an initial set of guidelines for the creation of the visual representation, including pitfalls and areas where the graphics can be enhanced through interactive exploration. Basic analytical methods are explored as a means of enhancing the visual analysis process, moving from visual analysis to visual analytics. Table of Contents: Data Types / Color Schemes / Data Preconditioning / Visual Representations and Analysis / Summary

Data Science Fundamentals and Practical Approaches

Author : Nandi Dr. Rupam Dr. Gypsy, Kumar Sharma
Publisher : BPB Publications
ISBN 13 : 938984567X
Total Pages : 580 pages
Book Rating : 4.3/5 (898 download)

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Book Synopsis Data Science Fundamentals and Practical Approaches by : Nandi Dr. Rupam Dr. Gypsy, Kumar Sharma

Download or read book Data Science Fundamentals and Practical Approaches written by Nandi Dr. Rupam Dr. Gypsy, Kumar Sharma and published by BPB Publications. This book was released on 2020-09-03 with total page 580 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to process and analysis data using Python Key Features a- The book has theories explained elaborately along with Python code and corresponding output to support the theoretical explanations. The Python codes are provided with step-by-step comments to explain each instruction of the code. a- The book is quite well balanced with programs and illustrative real-case problems. a- The book not only deals with the background mathematics alone or only the programs but also beautifully correlates the background mathematics to the theory and then finally translating it into the programs. a- A rich set of chapter-end exercises are provided, consisting of both short-answer questions and long-answer questions. Description This book introduces the fundamental concepts of Data Science, which has proved to be a major game-changer in business solving problems. Topics covered in the book include fundamentals of Data Science, data preprocessing, data plotting and visualization, statistical data analysis, machine learning for data analysis, time-series analysis, deep learning for Data Science, social media analytics, business analytics, and Big Data analytics. The content of the book describes the fundamentals of each of the Data Science related topics together with illustrative examples as to how various data analysis techniques can be implemented using different tools and libraries of Python programming language. Each chapter contains numerous examples and illustrative output to explain the important basic concepts. An appropriate number of questions is presented at the end of each chapter for self-assessing the conceptual understanding. The references presented at the end of every chapter will help the readers to explore more on a given topic. What will you learn a- Understand what machine learning is and how learning can be incorporated into a program. a- Perform data processing to make it ready for visual plot to understand the pattern in data over time. a- Know how tools can be used to perform analysis on big data using python a- Perform social media analytics, business analytics, and data analytics on any data of a company or organization. Who this book is for The book is for readers with basic programming and mathematical skills. The book is for any engineering graduates that wish to apply data science in their projects or wish to build a career in this direction. The book can be read by anyone who has an interest in data analysis and would like to explore more out of interest or to apply it to certain real-life problems. Table of Contents 1. Fundamentals of Data Science1 2. Data Preprocessing 3. Data Plotting and Visualization 4. Statistical Data Analysis 5. Machine Learning for Data Science 6. Time-Series Analysis 7. Deep Learning for Data Science 8. Social Media Analytics 9. Business Analytics 10. Big Data Analytics About the Authors Dr. Gypsy Nandi is an Assistant Professor (Sr) in the Department of Computer Applications, Assam Don Bosco University, India. Her areas of interest include Data Science, Social Network Mining, and Machine Learning. She has completed her Ph.D. in the field of 'Social Network Analysis and Mining'. Her research scholars are currently working mainly in the field of Data Science. She has several research publications in reputed journals and book series. Dr. Rupam Kumar Sharma is an Assistant Professor in the Department of Computer Applications, Assam Don Bosco University, India. His area of interest includes Machine Learning, Data Analytics, Network, and Cyber Security. He has several research publications in reputed SCI and Scopus journals. He has also delivered lectures and trained hundreds of trainees and students across different institutes in the field of security and android app development.

Big Data Benchmarks, Performance Optimization, and Emerging Hardware

Author : Jianfeng Zhan
Publisher : Springer
ISBN 13 : 3319130218
Total Pages : 227 pages
Book Rating : 4.3/5 (191 download)

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Book Synopsis Big Data Benchmarks, Performance Optimization, and Emerging Hardware by : Jianfeng Zhan

Download or read book Big Data Benchmarks, Performance Optimization, and Emerging Hardware written by Jianfeng Zhan and published by Springer. This book was released on 2014-11-10 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly revised selected papers of the 4th and 5th workshops on Big Data Benchmarks, Performance Optimization, and Emerging Hardware, BPOE 4 and BPOE 5, held respectively in Salt Lake City, in March 2014, and in Hangzhou, in September 2014. The 16 papers presented were carefully reviewed and selected from 30 submissions. Both workshops focus on architecture and system support for big data systems, such as benchmarking; workload characterization; performance optimization and evaluation; emerging hardware.

Languages and Compilers for Parallel Computing

Author : Bill Pugh
Publisher : Springer Science & Business Media
ISBN 13 : 3540307818
Total Pages : 386 pages
Book Rating : 4.5/5 (43 download)

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Book Synopsis Languages and Compilers for Parallel Computing by : Bill Pugh

Download or read book Languages and Compilers for Parallel Computing written by Bill Pugh and published by Springer Science & Business Media. This book was released on 2005-12-13 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-proceedings of the 15th International Workshop on Languages and Compilers for Parallel Processing, LCPC 2002, held in College Park, MD, USA in July 2002. The 26 revised full papers presented were carefully selected during two rounds of reviewing and improvement from 32 submissions. All current issues in parallel processing are addressed, in particular memory-constrained computation, compiler optimization, performance studies, high-level languages, programming language consistency models, dynamic parallelization, parallelization of data mining algorithms, parallelizing compilers, garbage collection algorithms, and evaluation of iterative compilation.

Gene Expression Data Analysis

Author : Pankaj Barah
Publisher : CRC Press
ISBN 13 : 1000425738
Total Pages : 379 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Gene Expression Data Analysis by : Pankaj Barah

Download or read book Gene Expression Data Analysis written by Pankaj Barah and published by CRC Press. This book was released on 2021-11-21 with total page 379 pages. Available in PDF, EPUB and Kindle. Book excerpt: Development of high-throughput technologies in molecular biology during the last two decades has contributed to the production of tremendous amounts of data. Microarray and RNA sequencing are two such widely used high-throughput technologies for simultaneously monitoring the expression patterns of thousands of genes. Data produced from such experiments are voluminous (both in dimensionality and numbers of instances) and evolving in nature. Analysis of huge amounts of data toward the identification of interesting patterns that are relevant for a given biological question requires high-performance computational infrastructure as well as efficient machine learning algorithms. Cross-communication of ideas between biologists and computer scientists remains a big challenge. Gene Expression Data Analysis: A Statistical and Machine Learning Perspective has been written with a multidisciplinary audience in mind. The book discusses gene expression data analysis from molecular biology, machine learning, and statistical perspectives. Readers will be able to acquire both theoretical and practical knowledge of methods for identifying novel patterns of high biological significance. To measure the effectiveness of such algorithms, we discuss statistical and biological performance metrics that can be used in real life or in a simulated environment. This book discusses a large number of benchmark algorithms, tools, systems, and repositories that are commonly used in analyzing gene expression data and validating results. This book will benefit students, researchers, and practitioners in biology, medicine, and computer science by enabling them to acquire in-depth knowledge in statistical and machine-learning-based methods for analyzing gene expression data. Key Features: An introduction to the Central Dogma of molecular biology and information flow in biological systems A systematic overview of the methods for generating gene expression data Background knowledge on statistical modeling and machine learning techniques Detailed methodology of analyzing gene expression data with an example case study Clustering methods for finding co-expression patterns from microarray, bulkRNA, and scRNA data A large number of practical tools, systems, and repositories that are useful for computational biologists to create, analyze, and validate biologically relevant gene expression patterns Suitable for multidisciplinary researchers and practitioners in computer science and biological sciences

OpenMP in the Era of Low Power Devices and Accelerators

Author : Alistair P. Rendell
Publisher : Springer
ISBN 13 : 364240698X
Total Pages : 210 pages
Book Rating : 4.6/5 (424 download)

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Book Synopsis OpenMP in the Era of Low Power Devices and Accelerators by : Alistair P. Rendell

Download or read book OpenMP in the Era of Low Power Devices and Accelerators written by Alistair P. Rendell and published by Springer. This book was released on 2013-08-15 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 9th International Workshop on OpenMP, held in Canberra, Australia, in September 2013. The 14 technical full papers presented were carefully reviewed and selected from various submissions. The papers are organized in topical sections on proposed extensions to OpenMP, applications, accelerators, scheduling, and tools.

Fiber Optics Standards

Author : IGIC, Inc. Staff
Publisher : Information Gatekeepers Inc
ISBN 13 : 9781568510590
Total Pages : 742 pages
Book Rating : 4.5/5 (15 download)

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Book Synopsis Fiber Optics Standards by : IGIC, Inc. Staff

Download or read book Fiber Optics Standards written by IGIC, Inc. Staff and published by Information Gatekeepers Inc. This book was released on 1994 with total page 742 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Artificial Intelligence for Big Data

Author : Anand Deshpande
Publisher : Packt Publishing Ltd
ISBN 13 : 1788476018
Total Pages : 371 pages
Book Rating : 4.7/5 (884 download)

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Book Synopsis Artificial Intelligence for Big Data by : Anand Deshpande

Download or read book Artificial Intelligence for Big Data written by Anand Deshpande and published by Packt Publishing Ltd. This book was released on 2018-05-22 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build next-generation Artificial Intelligence systems with Java Key Features Implement AI techniques to build smart applications using Deeplearning4j Perform big data analytics to derive quality insights using Spark MLlib Create self-learning systems using neural networks, NLP, and reinforcement learning Book Description In this age of big data, companies have larger amount of consumer data than ever before, far more than what the current technologies can ever hope to keep up with. However, Artificial Intelligence closes the gap by moving past human limitations in order to analyze data. With the help of Artificial Intelligence for big data, you will learn to use Machine Learning algorithms such as k-means, SVM, RBF, and regression to perform advanced data analysis. You will understand the current status of Machine and Deep Learning techniques to work on Genetic and Neuro-Fuzzy algorithms. In addition, you will explore how to develop Artificial Intelligence algorithms to learn from data, why they are necessary, and how they can help solve real-world problems. By the end of this book, you'll have learned how to implement various Artificial Intelligence algorithms for your big data systems and integrate them into your product offerings such as reinforcement learning, natural language processing, image recognition, genetic algorithms, and fuzzy logic systems. What you will learn Manage Artificial Intelligence techniques for big data with Java Build smart systems to analyze data for enhanced customer experience Learn to use Artificial Intelligence frameworks for big data Understand complex problems with algorithms and Neuro-Fuzzy systems Design stratagems to leverage data using Machine Learning process Apply Deep Learning techniques to prepare data for modeling Construct models that learn from data using open source tools Analyze big data problems using scalable Machine Learning algorithms Who this book is for This book is for you if you are a data scientist, big data professional, or novice who has basic knowledge of big data and wish to get proficiency in Artificial Intelligence techniques for big data. Some competence in mathematics is an added advantage in the field of elementary linear algebra and calculus.