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diego michel
diego michel

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5 books to learn algorithms and Data Structures

What is an Algorithm?
an algorithm (from the Latin, Dixit algorithms and this from the Greek arithmos, which means “number”, perhaps also influenced by the name of the Persian mathematician Al-Khuarismi) 1 is a set of defined and unambiguous instructions or rules, ordered and finite that allows, typically, to solve a problem, perform a computation, process data and carry out other tasks or activities.2 Given an initial state and an input, following the successive steps a final state is reached and a solution is obtained. Algorithms are the object of study of algorithm

1- 40 Algorithms Every Programmer Should Know
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Algorithms have always played an important role in both the science and practice of computing. Beyond traditional computing, the ability to use algorithms to solve real-world problems is an important skill that any developer or programmer must-have. This book will help you not only to develop the skills to select and use an algorithm to solve real-world problems but also to understand how it works.

You’ll start with an introduction to algorithms and discover various algorithm design techniques, before exploring how to implement different types of algorithms, such as searching and sorting, with the help of practical examples. As you advance to a more complex set of algorithms, you’ll learn about linear programming, page ranking, and graphs, and even work with machine learning algorithms, understanding the math and logic behind them.

Further on, case studies such as weather prediction, tweet clustering, and movie recommendation engines will show you how to apply these algorithms optimally. Finally, you’ll become well versed in techniques that enable parallel processing, giving you the ability to use these algorithms for compute-intensive tasks.

2-Advanced Algorithms and Data Structures
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Advanced Algorithms and Data Structures introduces a collection of algorithms for complex programming challenges in data analysis, machine learning, and graph computing. You’ll discover cutting-edge approaches to a variety of tricky scenarios. You’ll even learn to design your own data structures for projects that require a custom solution.

3- Learning Algorithms
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When it comes to writing efficient code, every software professional needs to have an effective working knowledge of algorithms. In this practical book, author George Heineman (Algorithms in a Nutshell) provides concise and informative descriptions of key algorithms that improve coding.

Software developers, testers, and maintainers will discover how algorithms solve computational problems creatively.

Each chapter builds on earlier chapters through eye-catching visuals and a steady rollout of essential concepts, including an algorithm analysis to classify the performance of every algorithm presented in the book.

At the end of each chapter, you’ll get to apply what you’ve learned to a novel challenge problem — simulating the experience you might find in a technical code interview.

4- Grokking Algorithms
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Grokking Algorithms is a friendly take on this core computer science topic. In it, you’ll learn how to apply common algorithms to the practical programming problems you face every day.

You’ll start with tasks like sorting and searching. As you build up your skills, you’ll tackle more complex problems like data compression and artificial intelligence. Each carefully presented example includes helpful diagrams and fully annotated code samples in Python.

By the end of this book, you will have mastered widely applicable algorithms as well as how and when to use them.

5- Dive Into Algorithms
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Dive Into Algorithms is a wide-ranging, Pythonic tour of many of the world’s most interesting algorithms. With little more than a bit of computer programming experience and basic high-school math, you’ll explore standard computer science algorithms for searching, sorting, and optimization; human-based algorithms that help us determine how to catch a baseball or eat the right amount at a buffet; and advanced algorithms like ones used in machine learning and artificial intelligence.

You’ll even explore how ancient Egyptians and Russian peasants used algorithms to multiply numbers, how the ancient Greeks used them to find greatest common divisors, and how Japanese scholars in the age of samurai designed algorithms capable of generating magic squares.

You’ll explore algorithms that are useful in pure mathematics and learn how mathematical ideas can improve algorithms. You’ll learn about an algorithm for generating continued fractions, one for quick calculations of square roots, and another for generating seemingly random sets of numbers.

Codeless Data Structures and Algorithms : Learn DSA Without Writing a Single Line of Code

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In the era of self-taught developers and programmers, essential topics in the industry are frequently learned without a formal academic foundation. A solid grasp of data structures and algorithms (DSA) is imperative for anyone looking to do professional software development and engineering, but classes in the subject can be dry or spend too much time on theory and unnecessary readings.

Regardless of your programming language background,Codeless Data Structures and Algorithms has you covered.

In everyday life, algorithms are frequently used to solve certain problems. Some examples are user manuals, which show algorithms for using a device, or instructions that a worker receives from his employer.

Some examples in mathematics are the multiplication algorithm, to calculate the product, the division algorithm to calculate the quotient of two numbers, the Euclid algorithm to obtain the greatest common divisor of two positive integers, or the Gaussian method to solve a system of linear equations.

In programming terms, an algorithm is a sequence of logical steps that allows you to solve a problem.

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