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Algorithms of the Intelligent Web, Second Edition
DESCRIPTION There's priceless insight trapped in the flood of data users leave behind as they interact with web pages and applications.Those insights can be unlocked by using intelligent algorithms like the ones that have earned Facebook, Google, Twitter, and Microsoft a place among the giants of web data pattern extraction.Improved search, data classification, and other smart pattern matching techniques can give an enormous advantage to understanding and interacting with users. Algorithms of the Intelligent Web, Second Edition has been totally revised and teaches the most important approaches to algorithmic web data analysis, enabling readers to create machine learning applications that crunch, munge, and wrangle data collected from users, web applications, sensors, and website logs.Key machine learning concepts are explained and introduced with many code examples in Python's scikit-learn.The book guides readers through the underlying machinery and intelligent algorithms to capture, store, and structure data streams.Readers will explore recommendation engines from the example of Netflix movie recommendations and dive into classification via statistical algorithms, neural networks, and deep learning.They will also consider the ins and outs of ranking and how to test applications based on intelligent algorithms. KEY SELLING POINTS Machine learning for newbies Easily accessed examples Concepts presented are technology agnostic AUDIENCE To get the most from this book, you should have a good foundation in Java programming and a general understanding of internet technology. ABOUT THE TECHNOLOGY This book provides an overview, with easy to access examples, of algorithms which learn from data.Such algorithms have been widely adopted by many large internet companies such as Facebook and Google and are continuing to grow in popularity.This book has many examples in Python using the scikit-learn library, however the concepts presented are technology agnostic and can be easily applied with any common programming language.
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Algorithms
Use your big monkey brain to do things that even your teachers can't do.With these books, you will talk to computers, create games, draw pictures and find information.Come on, code monkeys - let's write some code!
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Algorithms
Use your big monkey brain to do things that even your teachers can't do.With these books, you will talk to computers, create games, draw pictures and find information.Come on, code monkeys - let's write some code!
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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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Simple Algorithms
First Coding introduces children to the basic principles of programming and computing, from being safe on the internet to their first steps in computer logic.This series uses easy-to-read text and colourful images, as well as real examples of code.
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Optimization Algorithms
Solve design, planning, and control problems using modern machine learning and AI techniques. In Optimization Algorithms: AI techniques for design, planning, and control problems you will learn: Machine learning methods for search and optimization problemsThe core concepts of search and optimizationDeterministic and stochastic optimization techniquesGraph search algorithmsNature-inspired search and optimization algorithmsEfficient trade-offs between search space exploration and exploitationState-of-the-art Python libraries for search and optimization About the technology: Search and optimization algorithms are powerful tools that can help practitioners find optimal or near-optimal solutions to a wide range of design, planning and control problems.When you open a route planning app, call for a rideshare, or schedule a hospital appointment, an AI algorithm works behind the scenes to make sure you get an optimized result.This guide reveals the classical and modern algorithms behind these services.
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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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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 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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What are algorithms in computer science?
Algorithms in computer science are step-by-step procedures or formulas for solving a problem or accomplishing a task. They are a set of rules or instructions that are followed to achieve a particular goal. Algorithms are used in various computer science applications, such as sorting data, searching for information, and performing calculations. They are essential in programming and software development as they provide a systematic way to solve problems and process data efficiently.
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