Products related to Algorithms:
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Analytics: Business Intelligence, Algorithms and Statistical Analysis
Analytics - Business Intelligence, Algorithms and Statistical AnalysisIn today's world, analysis has become an extremely important aspect to consider when you are thinking of starting any new line of business or even when it comes to purchasing a new house. The unfortunate fact is that not many people know what analysis is all about.They tend to assume that each of the elements - analysis, business intelligence, algorithms and statistical analysis - are different entities when in reality they are all interlinked.This book will help you gather a greater insight on all the elements. And you will gain an in-depth knowledge on each of these elements in different parts of the book; helping you to increase your knowledge and widen your horizons!
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Big Data Analytics in Agriculture : Algorithms and Applications
Big Data Analytics in Agriculture: Algorithms and Applications focuses on quantitative and qualitative assessment using state-of-the-art technology to provide practical improvements to agricultural production.The book provides a complete mapping—from data generation to storage to curation, processing and implementation/application—to produce high-quality reliable information for decision-making.It follows a logical pathway to demonstrate how data contributes to a converging flow of information towards a decision support system and how it can be transformed into actionable steps. The book develops ideas surrounding a strong integration of ICT and IoT to manage rural assets to deliver improved economic and environmental performance in a spatially and temporarily variable environment.
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Data Analytics : Models and Algorithms for Intelligent Data Analysis
This book is a comprehensive introduction to the methods and algorithms of modern data analytics.It provides a sound mathematical basis, discusses advantages and drawbacks of different approaches, and enables the reader to design and implement data analytics solutions for real-world applications.This book has been used for more than ten years in the Data Mining course at the Technical University of Munich.Much of the content is based on the results of industrial research and development projects at Siemens.
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Algorithms
An accessible introduction to algorithms, explaining not just what they are but how they work, with examples from a wide range of application areas.Digital technology runs on algorithms, sets of instructions that describe how to do something efficiently.Application areas range from search engines to tournament scheduling, DNA sequencing, and machine learning.Arguing that every educated person today needs to have some understanding of algorithms and what they do, in this volume in the MIT Press Essential Knowledge series, Panos Louridas offers an introduction to algorithms that is accessible to the nonspecialist reader.Louridas explains not just what algorithms are but also how they work, offering a wide range of examples and keeping mathematics to a minimum. After discussing what an algorithm does and how its effectiveness can be measured, Louridas covers three of the most fundamental applications areas: graphs, which describe networks, from eighteenth-century problems to today's social networks; searching, and how to find the fastest way to search; and sorting, and the importance of choosing the best algorithm for particular tasks.He then presents larger-scale applications: PageRank, Google's founding algorithm; and neural networks and deep learning.Finally, Louridas describes how all algorithms are nothing more than simple moves with pen and paper, and how from such a humble foundation rise all their spectacular achievements.
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What do algorithms achieve?
Algorithms achieve the ability to process and analyze large amounts of data quickly and efficiently. They help in making predictions, identifying patterns, and solving complex problems. Algorithms are used in various fields such as finance, healthcare, and technology to optimize processes and improve decision-making. Overall, algorithms play a crucial role in automating tasks, improving productivity, and driving innovation.
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What do algorithms calculate?
Algorithms are designed to calculate specific tasks or operations based on a set of instructions. They can be used to perform mathematical calculations, process data, analyze patterns, make decisions, and solve problems. In essence, algorithms are used to automate and streamline various processes by following a predefined sequence of steps to produce a desired outcome.
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What are the Instagram algorithms?
The Instagram algorithms are a set of complex calculations used by the platform to determine what content users see on their feed. These algorithms analyze user behavior, such as likes, comments, and shares, to prioritize content from accounts that users engage with the most. The algorithms also take into account the timeliness of posts, the relationship between users, and the type of content being shared. By using these algorithms, Instagram aims to show users the most relevant and engaging content on their feed.
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Which sorting algorithms are there?
There are several common sorting algorithms, including bubble sort, selection sort, insertion sort, merge sort, quick sort, and heap sort. Each algorithm has its own advantages and disadvantages in terms of time complexity, space complexity, and stability. The choice of sorting algorithm depends on the specific requirements of the problem at hand.
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Orienteering Problems : Models and Algorithms for Vehicle Routing Problems with Profits
This tutorial introduces readers to several variants of routing problems with profits.In these routing problems each node has a certain profit, and not all nodes need to be visited.Since the orienteering problem (OP) is by far the most frequently studied problem in this category of routing problems, the book mainly focuses on the OP.In turn, other problems are presented as variants of the OP, focusing on the similarities and differences.The goal of the OP is to determine a subset of nodes to visit and in which order, so that the total collected profit is maximized and a given time budget is not exceeded.The book provides a comprehensive review of variants of the OP, such as the team OP, the team OP with time windows, the profitable tour problem, and the prize-collecting travelling salesperson problem.In addition, it presents mathematical models and techniques for solving these OP variants and discusses their complexity.Several simple examples and benchmark instances, together with their best-known results, are also included.Finally, the book reviews the latest applications of these problems in the fields of logistics, tourism and others.
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GIS Algorithms
Geographic information systems (GIS) have become increasingly important in helping us understand complex social, economic, and natural dynamics where spatial components play a key role.The critical algorithms used in GIS, however, are notoriously difficult to both teach and understand, in part due to the lack of a coherent representation.GIS Algorithms attempts to address this problem by combining rigorous formal language with example case studies and student exercises. Using Python code throughout, Xiao breaks the subject down into three fundamental areas:Geometric AlgorithmsSpatial IndexingSpatial Analysis and ModellingWith its comprehensive coverage of the many algorithms involved, GIS Algorithms is a key new textbook in this complex and critical area of geography.
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Algorithms Unlocked
For anyone who has ever wondered how computers solve problems, an engagingly written guide for nonexperts to the basics of computer algorithms. Have you ever wondered how your GPS can find the fastest way to your destination, selecting one route from seemingly countless possibilities in mere seconds?How your credit card account number is protected when you make a purchase over the Internet?The answer is algorithms. And how do these mathematical formulations translate themselves into your GPS, your laptop, or your smart phone?This book offers an engagingly written guide to the basics of computer algorithms.In Algorithms Unlocked, Thomas Cormen-coauthor of the leading college textbook on the subject-provides a general explanation, with limited mathematics, of how algorithms enable computers to solve problems. Readers will learn what computer algorithms are, how to describe them, and how to evaluate them.They will discover simple ways to search for information in a computer; methods for rearranging information in a computer into a prescribed order ("sorting"); how to solve basic problems that can be modeled in a computer with a mathematical structure called a "graph" (useful for modeling road networks, dependencies among tasks, and financial relationships); how to solve problems that ask questions about strings of characters such as DNA structures; the basic principles behind cryptography; fundamentals of data compression; and even that there are some problems that no one has figured out how to solve on a computer in a reasonable amount of time.
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Parallel Algorithms
This book is an introduction to the field of parallel algorithms and the underpinning techniques to realize the parallelization.The emphasis is on designing algorithms within the timeless and abstracted context of a high-level programming language.The focus of the presentation is on practical applications of the algorithm design using different models of parallel computation.Each model is illustrated by providing an adequate number of algorithms to solve some problems that quite often arise in many applications in science and engineering.The book is largely self-contained, presuming no special knowledge of parallel computers or particular mathematics.In addition, the solutions to all exercises are included at the end of each chapter.The book is intended as a text in the field of the design and analysis of parallel algorithms.It includes adequate material for a course in parallel algorithms at both undergraduate and graduate levels.
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Should one learn without algorithms?
Learning without algorithms is certainly possible, as there are many different ways to acquire knowledge and skills. However, algorithms can be valuable tools for organizing and processing information, so learning about them can be beneficial. Understanding algorithms can help individuals solve complex problems, improve decision-making processes, and enhance their overall problem-solving abilities. Therefore, while it is not necessary to learn algorithms, doing so can certainly be advantageous in many fields.
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What is spatial visualization ability?
Spatial visualization ability refers to the capacity to mentally manipulate and comprehend spatial relationships between objects. Individuals with strong spatial visualization skills can easily visualize and understand how objects relate to each other in space, such as rotating or manipulating shapes in their mind. This ability is crucial in various fields such as engineering, architecture, and mathematics, as it allows individuals to solve complex problems and understand spatial concepts more effectively. Improving spatial visualization ability can enhance problem-solving skills and overall cognitive performance.
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What are simple algorithms in Java?
Simple algorithms in Java are step-by-step procedures for solving a specific problem or performing a specific task. These algorithms are typically written in Java programming language and are designed to be easy to understand and implement. Examples of simple algorithms in Java include sorting algorithms like bubble sort or insertion sort, searching algorithms like linear search or binary search, and mathematical algorithms like finding the factorial of a number or calculating the Fibonacci sequence. These algorithms are fundamental building blocks in computer science and are essential for solving a wide range of problems in software development.
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How do logarithmic sorting algorithms work?
Logarithmic sorting algorithms work by dividing the input data into smaller subgroups and recursively sorting these subgroups. One common example is the merge sort algorithm, which divides the input list into two halves, sorts each half separately, and then merges them back together in sorted order. By repeatedly dividing the data and merging the sorted subgroups, logarithmic sorting algorithms achieve a time complexity of O(n log n), making them efficient for large datasets.
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