Tools For Chemical Product Design

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Author :
Publisher : Elsevier
ISBN 13 : 0444636846
Total Pages : 702 pages
Book Rating : 4.4/5 (446 download)

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Book Synopsis Tools For Chemical Product Design by : Mariano Martín Martín

Download or read book Tools For Chemical Product Design written by Mariano Martín Martín and published by Elsevier. This book was released on 2016-09-19 with total page 702 pages. Available in PDF, EPUB and Kindle. Book excerpt: Tools for Chemical Product Design: From Consumer Products to Biomedicine describes the challenges involved in systematic product design across a variety of industries and provides a comprehensive overview of mathematical tools aimed at the design of chemical products, from molecular design to customer products. Chemical product design has become increasingly important over the past decade and includes a wide range of sectors including gasoline additives and blends in the petroleum industry, active ingredients and excipients in the pharmaceutical industry, and a variety of consumer products and specialty chemicals. Traditionally, such products have been designed through trial and error methods, which not only are time-consuming, but more importantly only provide limited knowledge that can be translated into next generation products. - Features an impressive collection of contributions from leading researchers in the field - Presents the latest tools available across a variety of industries - Describes the challenges involved in systematic product design as well as the latest methods for solving such problems - Covers a wide range of sectors including gasoline additives and blends in the petroleum industry, active ingredients and excipients in the pharmaceutical industry, and a variety of consumer products and specialty chemicals

Ant Colony Optimization

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Author :
Publisher : MIT Press
ISBN 13 : 9780262042192
Total Pages : 324 pages
Book Rating : 4.0/5 (421 download)

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Book Synopsis Ant Colony Optimization by : Marco Dorigo

Download or read book Ant Colony Optimization written by Marco Dorigo and published by MIT Press. This book was released on 2004-06-04 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: An overview of the rapidly growing field of ant colony optimization that describes theoretical findings, the major algorithms, and current applications. The complex social behaviors of ants have been much studied by science, and computer scientists are now finding that these behavior patterns can provide models for solving difficult combinatorial optimization problems. The attempt to develop algorithms inspired by one aspect of ant behavior, the ability to find what computer scientists would call shortest paths, has become the field of ant colony optimization (ACO), the most successful and widely recognized algorithmic technique based on ant behavior. This book presents an overview of this rapidly growing field, from its theoretical inception to practical applications, including descriptions of many available ACO algorithms and their uses. The book first describes the translation of observed ant behavior into working optimization algorithms. The ant colony metaheuristic is then introduced and viewed in the general context of combinatorial optimization. This is followed by a detailed description and guide to all major ACO algorithms and a report on current theoretical findings. The book surveys ACO applications now in use, including routing, assignment, scheduling, subset, machine learning, and bioinformatics problems. AntNet, an ACO algorithm designed for the network routing problem, is described in detail. The authors conclude by summarizing the progress in the field and outlining future research directions. Each chapter ends with bibliographic material, bullet points setting out important ideas covered in the chapter, and exercises. Ant Colony Optimization will be of interest to academic and industry researchers, graduate students, and practitioners who wish to learn how to implement ACO algorithms.

Advanced Optimization by Nature-Inspired Algorithms

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Author :
Publisher : Springer
ISBN 13 : 9811052212
Total Pages : 166 pages
Book Rating : 4.8/5 (11 download)

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Book Synopsis Advanced Optimization by Nature-Inspired Algorithms by : Omid Bozorg-Haddad

Download or read book Advanced Optimization by Nature-Inspired Algorithms written by Omid Bozorg-Haddad and published by Springer. This book was released on 2017-06-30 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book, compiles, presents, and explains the most important meta-heuristic and evolutionary optimization algorithms whose successful performance has been proven in different fields of engineering, and it includes application of these algorithms to important engineering optimization problems. In addition, this book guides readers to studies that have implemented these algorithms by providing a literature review on developments and applications of each algorithm. This book is intended for students, but can be used by researchers and professionals in the area of engineering optimization.

Biologically Rationalized Computing Techniques For Image Processing Applications

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Author :
Publisher : Springer
ISBN 13 : 3319613162
Total Pages : 341 pages
Book Rating : 4.3/5 (196 download)

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Book Synopsis Biologically Rationalized Computing Techniques For Image Processing Applications by : Jude Hemanth

Download or read book Biologically Rationalized Computing Techniques For Image Processing Applications written by Jude Hemanth and published by Springer. This book was released on 2017-08-15 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces readers to innovative bio-inspired computing techniques for image processing applications. It demonstrates how a significant drawback of image processing – not providing the simultaneous benefits of high accuracy and less complexity – can be overcome, proposing bio-inspired methodologies to help do so. Besides computing techniques, the book also sheds light on the various application areas related to image processing, and weighs the pros and cons of specific methodologies. Even though several such methodologies are available, most of them do not provide the simultaneous benefits of high accuracy and less complexity, which explains their low usage in connection with practical imaging applications, such as the medical scenario. Lastly, the book illustrates the methodologies in detail, making it suitable for newcomers to the field and advanced researchers alike.

Stochastic Local Search

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Author :
Publisher : Morgan Kaufmann
ISBN 13 : 1558608729
Total Pages : 678 pages
Book Rating : 4.5/5 (586 download)

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Book Synopsis Stochastic Local Search by : Holger H. Hoos

Download or read book Stochastic Local Search written by Holger H. Hoos and published by Morgan Kaufmann. This book was released on 2005 with total page 678 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic local search (SLS) algorithms are among the most prominent and successful techniques for solving computationally difficult problems. Offering a systematic treatment of SLS algorithms, this book examines the general concepts and specific instances of SLS algorithms and considers their development, analysis and application.

Swarm Intelligence and Bio-Inspired Computation

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Author :
Publisher : Newnes
ISBN 13 : 0124051774
Total Pages : 445 pages
Book Rating : 4.1/5 (24 download)

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Book Synopsis Swarm Intelligence and Bio-Inspired Computation by : Xin-She Yang

Download or read book Swarm Intelligence and Bio-Inspired Computation written by Xin-She Yang and published by Newnes. This book was released on 2013-05-16 with total page 445 pages. Available in PDF, EPUB and Kindle. Book excerpt: Swarm Intelligence and bio-inspired computation have become increasing popular in the last two decades. Bio-inspired algorithms such as ant colony algorithms, bat algorithms, bee algorithms, firefly algorithms, cuckoo search and particle swarm optimization have been applied in almost every area of science and engineering with a dramatic increase of number of relevant publications. This book reviews the latest developments in swarm intelligence and bio-inspired computation from both the theory and application side, providing a complete resource that analyzes and discusses the latest and future trends in research directions. It can help new researchers to carry out timely research and inspire readers to develop new algorithms. With its impressive breadth and depth, this book will be useful for advanced undergraduate students, PhD students and lecturers in computer science, engineering and science as well as researchers and engineers. - Focuses on the introduction and analysis of key algorithms - Includes case studies for real-world applications - Contains a balance of theory and applications, so readers who are interested in either algorithm or applications will all benefit from this timely book.

Handbook of Swarm Intelligence

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Author :
Publisher : Springer Science & Business Media
ISBN 13 : 364217390X
Total Pages : 538 pages
Book Rating : 4.6/5 (421 download)

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Book Synopsis Handbook of Swarm Intelligence by : Bijaya Ketan Panigrahi

Download or read book Handbook of Swarm Intelligence written by Bijaya Ketan Panigrahi and published by Springer Science & Business Media. This book was released on 2011-02-04 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt: From nature, we observe swarming behavior in the form of ant colonies, bird flocking, animal herding, honey bees, swarming of bacteria, and many more. It is only in recent years that researchers have taken notice of such natural swarming systems as culmination of some form of innate collective intelligence, albeit swarm intelligence (SI) - a metaphor that inspires a myriad of computational problem-solving techniques. In computational intelligence, swarm-like algorithms have been successfully applied to solve many real-world problems in engineering and sciences. This handbook volume serves as a useful foundational as well as consolidatory state-of-art collection of articles in the field from various researchers around the globe. It has a rich collection of contributions pertaining to the theoretical and empirical study of single and multi-objective variants of swarm intelligence based algorithms like particle swarm optimization (PSO), ant colony optimization (ACO), bacterial foraging optimization algorithm (BFOA), honey bee social foraging algorithms, and harmony search (HS). With chapters describing various applications of SI techniques in real-world engineering problems, this handbook can be a valuable resource for researchers and practitioners, giving an in-depth flavor of what SI is capable of achieving.

Recent Advances in Swarm Intelligence and Evolutionary Computation

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Author :
Publisher : Springer
ISBN 13 : 331913826X
Total Pages : 295 pages
Book Rating : 4.3/5 (191 download)

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Book Synopsis Recent Advances in Swarm Intelligence and Evolutionary Computation by : Xin-She Yang

Download or read book Recent Advances in Swarm Intelligence and Evolutionary Computation written by Xin-She Yang and published by Springer. This book was released on 2014-12-27 with total page 295 pages. Available in PDF, EPUB and Kindle. Book excerpt: This timely review volume summarizes the state-of-the-art developments in nature-inspired algorithms and applications with the emphasis on swarm intelligence and bio-inspired computation. Topics include the analysis and overview of swarm intelligence and evolutionary computation, hybrid metaheuristic algorithms, bat algorithm, discrete cuckoo search, firefly algorithm, particle swarm optimization, and harmony search as well as convergent hybridization. Application case studies have focused on the dehydration of fruits and vegetables by the firefly algorithm and goal programming, feature selection by the binary flower pollination algorithm, job shop scheduling, single row facility layout optimization, training of feed-forward neural networks, damage and stiffness identification, synthesis of cross-ambiguity functions by the bat algorithm, web document clustering, truss analysis, water distribution networks, sustainable building designs and others. As a timely review, this book can serve as an ideal reference for graduates, lecturers, engineers and researchers in computer science, evolutionary computing, artificial intelligence, machine learning, computational intelligence, data mining, engineering optimization and designs.

Algorithms for Optimization

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Publisher : MIT Press
ISBN 13 : 0262039427
Total Pages : 521 pages
Book Rating : 4.2/5 (62 download)

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Book Synopsis Algorithms for Optimization by : Mykel J. Kochenderfer

Download or read book Algorithms for Optimization written by Mykel J. Kochenderfer and published by MIT Press. This book was released on 2019-03-12 with total page 521 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive introduction to optimization with a focus on practical algorithms for the design of engineering systems. This book offers a comprehensive introduction to optimization with a focus on practical algorithms. The book approaches optimization from an engineering perspective, where the objective is to design a system that optimizes a set of metrics subject to constraints. Readers will learn about computational approaches for a range of challenges, including searching high-dimensional spaces, handling problems where there are multiple competing objectives, and accommodating uncertainty in the metrics. Figures, examples, and exercises convey the intuition behind the mathematical approaches. The text provides concrete implementations in the Julia programming language. Topics covered include derivatives and their generalization to multiple dimensions; local descent and first- and second-order methods that inform local descent; stochastic methods, which introduce randomness into the optimization process; linear constrained optimization, when both the objective function and the constraints are linear; surrogate models, probabilistic surrogate models, and using probabilistic surrogate models to guide optimization; optimization under uncertainty; uncertainty propagation; expression optimization; and multidisciplinary design optimization. Appendixes offer an introduction to the Julia language, test functions for evaluating algorithm performance, and mathematical concepts used in the derivation and analysis of the optimization methods discussed in the text. The book can be used by advanced undergraduates and graduate students in mathematics, statistics, computer science, any engineering field, (including electrical engineering and aerospace engineering), and operations research, and as a reference for professionals.

Adaptation in Natural and Artificial Systems

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Publisher : MIT Press
ISBN 13 : 9780262581110
Total Pages : 236 pages
Book Rating : 4.5/5 (811 download)

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Book Synopsis Adaptation in Natural and Artificial Systems by : John H. Holland

Download or read book Adaptation in Natural and Artificial Systems written by John H. Holland and published by MIT Press. This book was released on 1992-04-29 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: Genetic algorithms are playing an increasingly important role in studies of complex adaptive systems, ranging from adaptive agents in economic theory to the use of machine learning techniques in the design of complex devices such as aircraft turbines and integrated circuits. Adaptation in Natural and Artificial Systems is the book that initiated this field of study, presenting the theoretical foundations and exploring applications. In its most familiar form, adaptation is a biological process, whereby organisms evolve by rearranging genetic material to survive in environments confronting them. In this now classic work, Holland presents a mathematical model that allows for the nonlinearity of such complex interactions. He demonstrates the model's universality by applying it to economics, physiological psychology, game theory, and artificial intelligence and then outlines the way in which this approach modifies the traditional views of mathematical genetics. Initially applying his concepts to simply defined artificial systems with limited numbers of parameters, Holland goes on to explore their use in the study of a wide range of complex, naturally occuring processes, concentrating on systems having multiple factors that interact in nonlinear ways. Along the way he accounts for major effects of coadaptation and coevolution: the emergence of building blocks, or schemata, that are recombined and passed on to succeeding generations to provide, innovations and improvements.

Bio-Inspired Computational Algorithms and Their Applications

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Author :
Publisher : BoD – Books on Demand
ISBN 13 : 9535102141
Total Pages : 436 pages
Book Rating : 4.5/5 (351 download)

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Book Synopsis Bio-Inspired Computational Algorithms and Their Applications by : Shangce Gao

Download or read book Bio-Inspired Computational Algorithms and Their Applications written by Shangce Gao and published by BoD – Books on Demand. This book was released on 2012-03-07 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bio-inspired computational algorithms are always hot research topics in artificial intelligence communities. Biology is a bewildering source of inspiration for the design of intelligent artifacts that are capable of efficient and autonomous operation in unknown and changing environments. It is difficult to resist the fascination of creating artifacts that display elements of lifelike intelligence, thus needing techniques for control, optimization, prediction, security, design, and so on. Bio-Inspired Computational Algorithms and Their Applications is a compendium that addresses this need. It integrates contrasting techniques of genetic algorithms, artificial immune systems, particle swarm optimization, and hybrid models to solve many real-world problems. The works presented in this book give insights into the creation of innovative improvements over algorithm performance, potential applications on various practical tasks, and combination of different techniques. The book provides a reference to researchers, practitioners, and students in both artificial intelligence and engineering communities, forming a foundation for the development of the field.

Bionanotechnology

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Publisher : John Wiley & Sons
ISBN 13 : 0471469580
Total Pages : 351 pages
Book Rating : 4.4/5 (714 download)

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Book Synopsis Bionanotechnology by : David S. Goodsell

Download or read book Bionanotechnology written by David S. Goodsell and published by John Wiley & Sons. This book was released on 2004-04-16 with total page 351 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discussions of the basic structural, nanotechnology, and system engineering principles, as well as an introductory overview of essential concepts and methods in biotechnology, will be included. Text is presented side-by-side with extensive use of high-quality illustrations prepared using cutting edge computer graphics techniques. Includes numerous examples, such applications in genetic engineering. Represents the only available introduction and overview of this interdisciplinary field, merging the physical and biological sciences. Concludes with the authors' expert assessment of the future promise of nanotechnology, from molecular "tinkertoys" to nanomedicine. David Goodsell is author of two trade books, Machinery of Life and Our Molecular Nature, and Arthur Olson is the world's leader in molecular graphics and nano-scale representation.

Genetic Algorithms in Search, Optimization, and Machine Learning

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Author :
Publisher : Addison-Wesley Professional
ISBN 13 :
Total Pages : 436 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Genetic Algorithms in Search, Optimization, and Machine Learning by : David Edward Goldberg

Download or read book Genetic Algorithms in Search, Optimization, and Machine Learning written by David Edward Goldberg and published by Addison-Wesley Professional. This book was released on 1989 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: A gentle introduction to genetic algorithms. Genetic algorithms revisited: mathematical foundations. Computer implementation of a genetic algorithm. Some applications of genetic algorithms. Advanced operators and techniques in genetic search. Introduction to genetics-based machine learning. Applications of genetics-based machine learning. A look back, a glance ahead. A review of combinatorics and elementary probability. Pascal with random number generation for fortran, basic, and cobol programmers. A simple genetic algorithm (SGA) in pascal. A simple classifier system(SCS) in pascal. Partition coefficient transforms for problem-coding analysis.

Harmony Search Algorithm

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Author :
Publisher : Springer
ISBN 13 : 9811037280
Total Pages : 368 pages
Book Rating : 4.8/5 (11 download)

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Book Synopsis Harmony Search Algorithm by : Javier Del Ser

Download or read book Harmony Search Algorithm written by Javier Del Ser and published by Springer. This book was released on 2017-01-20 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents state-of-the-art technical contributions based around one of the most successful evolutionary optimization algorithms published to date: Harmony Search. Contributions span from novel technical derivations of this algorithm to applications in the broad fields of civil engineering, energy, transportation & mobility and health, among many others and focus not only on its cross-domain applicability, but also on its core evolutionary operators, including elements inspired from other meta-heuristics. The global scientific community is witnessing an upsurge in groundbreaking, new advances in all areas of computational intelligence, with a particular flurry of research focusing on evolutionary computation and bio-inspired optimization. Observed processes in nature and sociology have provided the basis for innovative algorithmic developments aimed at leveraging the inherent capability to adapt characterized by various animals, including ants, fireflies, wolves and humans. However, it is the behavioral patterns observed in music composition that motivated the advent of the Harmony Search algorithm, a meta-heuristic optimization algorithm that over the last decade has been shown to dominate other solvers in a plethora of application scenarios. The book consists of a selection of the best contributions presented at ICHSA, a major biannual event where leading global experts on meta-heuristic optimization present their latest findings and discuss the past, present, and future of the exciting field of Harmony Search optimization. It provides a valuable reference resource for researchers working in the field of optimization meta-heuristics, and a solid technical base for frontline investigations around this algorithm.

Constraint-Handling in Evolutionary Optimization

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Author :
Publisher : Springer Science & Business Media
ISBN 13 : 3642006183
Total Pages : 273 pages
Book Rating : 4.6/5 (42 download)

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Book Synopsis Constraint-Handling in Evolutionary Optimization by : Efrén Mezura-Montes

Download or read book Constraint-Handling in Evolutionary Optimization written by Efrén Mezura-Montes and published by Springer Science & Business Media. This book was released on 2009-04-07 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is the result of a special session on constraint-handling techniques used in evolutionary algorithms within the Congress on Evolutionary Computation (CEC) in 2007. It presents recent research in constraint-handling in evolutionary optimization.

The Wisdom of the Hive

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Author :
Publisher : Harvard University Press
ISBN 13 : 0674043405
Total Pages : 318 pages
Book Rating : 4.6/5 (74 download)

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Book Synopsis The Wisdom of the Hive by : Thomas D Seeley

Download or read book The Wisdom of the Hive written by Thomas D Seeley and published by Harvard University Press. This book was released on 2009-06-30 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes and illustrates the results of more than fifteen years of elegant experimental studies conducted by the author to investigate how a colony of bees is organized to gather its resources. The results of his research--including studies of the shaking signal, tremble dance, and waggle dance--offer the clearest, most detailed picture available of how a highly integrated animal society works.

Machine Learning Models and Algorithms for Big Data Classification

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Author :
Publisher : Springer
ISBN 13 : 1489976418
Total Pages : 364 pages
Book Rating : 4.4/5 (899 download)

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Book Synopsis Machine Learning Models and Algorithms for Big Data Classification by : Shan Suthaharan

Download or read book Machine Learning Models and Algorithms for Big Data Classification written by Shan Suthaharan and published by Springer. This book was released on 2015-10-20 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents machine learning models and algorithms to address big data classification problems. Existing machine learning techniques like the decision tree (a hierarchical approach), random forest (an ensemble hierarchical approach), and deep learning (a layered approach) are highly suitable for the system that can handle such problems. This book helps readers, especially students and newcomers to the field of big data and machine learning, to gain a quick understanding of the techniques and technologies; therefore, the theory, examples, and programs (Matlab and R) presented in this book have been simplified, hardcoded, repeated, or spaced for improvements. They provide vehicles to test and understand the complicated concepts of various topics in the field. It is expected that the readers adopt these programs to experiment with the examples, and then modify or write their own programs toward advancing their knowledge for solving more complex and challenging problems. The presentation format of this book focuses on simplicity, readability, and dependability so that both undergraduate and graduate students as well as new researchers, developers, and practitioners in this field can easily trust and grasp the concepts, and learn them effectively. It has been written to reduce the mathematical complexity and help the vast majority of readers to understand the topics and get interested in the field. This book consists of four parts, with the total of 14 chapters. The first part mainly focuses on the topics that are needed to help analyze and understand data and big data. The second part covers the topics that can explain the systems required for processing big data. The third part presents the topics required to understand and select machine learning techniques to classify big data. Finally, the fourth part concentrates on the topics that explain the scaling-up machine learning, an important solution for modern big data problems.