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Learning Javascript Data Structures And Algorithms

Author: Loiane Groner
Publisher: Packt Publishing Ltd
ISBN: 178355388X
Size: 13.85 MB
Format: PDF, ePub
View: 7420
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Hone your skills by learning classic data structures and algorithms in JavaScript About This Book Understand common data structures and the associated algorithms, as well as the context in which they are used. Master existing JavaScript data structures such as array, set and map and learn how to implement new ones such as stacks, linked lists, trees and graphs. All concepts are explained in an easy way, followed by examples. Who This Book Is For If you are a student of Computer Science or are at the start of your technology career and want to explore JavaScript's optimum ability, this book is for you. You need a basic knowledge of JavaScript and programming logic to start having fun with algorithms. What You Will Learn Declare, initialize, add, and remove items from arrays, stacks, and queues Get the knack of using algorithms such as DFS (Depth-first Search) and BFS (Breadth-First Search) for the most complex data structures Harness the power of creating linked lists, doubly linked lists, and circular linked lists Store unique elements with hash tables, dictionaries, and sets Use binary trees and binary search trees Sort data structures using a range of algorithms such as bubble sort, insertion sort, and quick sort In Detail This book begins by covering basics of the JavaScript language and introducing ECMAScript 7, before gradually moving on to the current implementations of ECMAScript 6. You will gain an in-depth knowledge of how hash tables and set data structure functions, as well as how trees and hash maps can be used to search files in a HD or represent a database. This book is an accessible route deeper into JavaScript. Graphs being one of the most complex data structures you'll encounter, we'll also give you a better understanding of why and how graphs are largely used in GPS navigation systems in social networks. Toward the end of the book, you'll discover how all the theories presented by this book can be applied in real-world solutions while working on your own computer networks and Facebook searches. Style and approach This book gets straight to the point, providing you with examples of how a data structure or algorithm can be used and giving you real-world applications of the algorithm in JavaScript. With real-world use cases associated with each data structure, the book explains which data structure should be used to achieve the desired results in the real world.

Learning Javascript Data Structures And Algorithms Second Edition

Author: Loiane Groner
Publisher: Packt Publishing
ISBN: 9781785285493
Size: 16.45 MB
Format: PDF, ePub
View: 1418
Download and Read
Hone your skills by learning classic data structures and algorithms in JavaScriptAbout This Book- Understand common data structures and the associated algorithms, as well as the context in which they are used.- Master existing JavaScript data structures such as array, set and map and learn how to implement new ones such as stacks, linked lists, trees and graphs.- All concepts are explained in an easy way, followed by examples.Who This Book Is ForIf you are a student of Computer Science or are at the start of your technology career and want to explore JavaScript's optimum ability, this book is for you. You need a basic knowledge of JavaScript and programming logic to start having fun with algorithms.What You Will Learn- Declare, initialize, add, and remove items from arrays, stacks, and queues- Get the knack of using algorithms such as DFS (Depth-first Search) and BFS (Breadth-First Search) for the most complex data structures- Harness the power of creating linked lists, doubly linked lists, and circular linked lists- Store unique elements with hash tables, dictionaries, and sets- Use binary trees and binary search trees- Sort data structures using a range of algorithms such as bubble sort, insertion sort, and quick sortIn DetailThis book begins by covering basics of the JavaScript language and introducing ECMAScript 7, before gradually moving on to the current implementations of ECMAScript 6. You will gain an in-depth knowledge of how hash tables and set data structure functions, as well as how trees and hash maps can be used to search files in a HD or represent a database. This book is an accessible route deeper into JavaScript. Graphs being one of the most complex data structures you'll encounter, we'll also give you a better understanding of why and how graphs are largely used in GPS navigation systems in social networks.Toward the end of the book, you'll discover how all the theories presented by this book can be applied in real-world solutions while working on your own computer networks and Facebook searches.Style and approachThis book gets straight to the point, providing you with examples of how a data structure or algorithm can be used and giving you real-world applications of the algorithm in JavaScript. With real-world use cases associated with each data structure, the book explains which data structure should be used to achieve the desired results in the real world.

Learn Ecmascript

Author: Narayan Prusty
Publisher: Packt Publishing Ltd
ISBN: 1788629620
Size: 40.62 MB
Format: PDF
View: 3361
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Get up and running with all the new features of ECMAScript and explore new ways of coding with JavaScript. Key Features Grasp the latest features of ECMAScript and the best way to use it in production code Learn newly added native APIs to JS Engine and perform tasks efficiently with a cleaner code base Understand the more complex sides of JavaScript such as the inheritance model, low-level memory management, multithreaded environments, and web workers Book Description Learn ECMAScript explores implementation of the latest ECMAScript features to add to your developer toolbox, helping you to progress to an advanced level. Learn to add 1 to a variable andsafely access shared memory data within multiple threads to avoid race conditions. You’ll start the book by building on your existing knowledge of JavaScript, covering performing arithmetic operations, using arrow functions and dealing with closures. Next, you will grasp the most commonly used ECMAScript skills such as reflection, proxies, and classes. Furthermore, you’ll learn modularizing the JS code base, implementing JS on the web and how the modern HTML5 + JS APIs provide power to developers on the web. Finally, you will learn the deeper parts of the language, which include making JavaScript multithreaded with dedicated and shared web workers, memory management, shared memory, and atomics. It doesn’t end here; this book is 100% compatible with ES.Next. By the end of this book, you'll have fully mastered all the features of ECMAScript! What you will learn Implement methods associated with objects as per the latest ECMAScript specification Make use of the latest features of ECMAScript Make use of many new APIs in HTML5 and modern JavaScript implementation Use SharedArrayBuffers for superfast concurrent and parallel programming Perform asynchronous programming with JavaScript Implement the best ways and practices to perform modular programming in JavaScript Who this book is for This book is for web developers who have some basic programming knowledge and want to learn to write cleaner code with the power of ECMAScript.

Mastering Ext Js Second Edition

Author: Loiane Groner
Publisher: Packt Publishing Ltd
ISBN: 1784399434
Size: 72.24 MB
Format: PDF, Docs
View: 7099
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If you are a developer who is familiar with Ext JS and want to augment your skills to create even better web applications, this is the book for you. Basic knowledge of JavaScript/HTML/CSS and any server-side language (PHP, Java, C#, Ruby, or Python) is required.

Javascript Regular Expressions

Author: Loiane Groner
Publisher: Packt Publishing Ltd
ISBN: 1783282266
Size: 46.56 MB
Format: PDF, ePub, Docs
View: 4330
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This book is ideal for JavaScript developers and programmers who work with any type of user entry data and want sharpen their skills to become experts.

Data Structures And Algorithms A First Course

Author: Iain T. Adamson
Publisher: Springer Science & Business Media
ISBN: 1447110234
Size: 58.87 MB
Format: PDF, Mobi
View: 436
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All young computer scientists who aspire to write programs must learn something about algorithms and data structures. This book does exactly that. Based on lecture courses developed by the author over a number of years the book is written in an informal and friendly way specifically to appeal to students. The book is divided into four parts: the first on Data Structures introduces a variety of structures and the fundamental operations associated with them, together with descriptions of how they are implemented in Pascal; the second discusses algorithms and the notion of complexity; Part III is concerned with the description of successively more elaborate structures for the storage of records and algorithms for retrieving a record from such a structure by means of its key; and finally, Part IV consists of very full solutions to nearly all the exercises in the book.

Deep Learning With Tensorflow

Author: Giancarlo Zaccone
Publisher: Packt Publishing Ltd
ISBN: 1788831837
Size: 62.62 MB
Format: PDF
View: 3058
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Delve into neural networks, implement deep learning algorithms, and explore layers of data abstraction with the help of TensorFlow. Key Features Learn how to implement advanced techniques in deep learning with Google's brainchild, TensorFlow Explore deep neural networks and layers of data abstraction with the help of this comprehensive guide Gain real-world contextualization through some deep learning problems concerning research and application Book Description Deep learning is a branch of machine learning algorithms based on learning multiple levels of abstraction. Neural networks, which are at the core of deep learning, are being used in predictive analytics, computer vision, natural language processing, time series forecasting, and to perform a myriad of other complex tasks. This book is conceived for developers, data analysts, machine learning practitioners and deep learning enthusiasts who want to build powerful, robust, and accurate predictive models with the power of TensorFlow, combined with other open source Python libraries. Throughout the book, you’ll learn how to develop deep learning applications for machine learning systems using Feedforward Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Autoencoders, and Factorization Machines. Discover how to attain deep learning programming on GPU in a distributed way. You'll come away with an in-depth knowledge of machine learning techniques and the skills to apply them to real-world projects. What you will learn Apply deep machine intelligence and GPU computing with TensorFlow Access public datasets and use TensorFlow to load, process, and transform the data Discover how to use the high-level TensorFlow API to build more powerful applications Use deep learning for scalable object detection and mobile computing Train machines quickly to learn from data by exploring reinforcement learning techniques Explore active areas of deep learning research and applications Who this book is for The book is for people interested in machine learning and machine intelligence. A rudimentary level of programming in one language is assumed, as is a basic familiarity with computer science techniques and technologies, including a basic awareness of computer hardware and algorithms. Some competence in mathematics is needed to the level of elementary linear algebra and calculus.