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JavaScript Data Structures and Algorithms
JavaScript Data Structures and Algorithms

Explore data structures and algorithm concepts and their relation to everyday JavaScript development. A basic understanding of these ideas is essential to any JavaScript developer wishing to analyze and build great software solutions. You'll discover how to implement data structures such as hash tables, linked lists, stacks, queues, trees, and graphs. You'll also learn how a URL shortener, such as bit.ly, is developed and what is happening to the data as a PDF is uploaded to a webpage. This book covers the practical applications of data structures and algorithms to encryption, searching, sorting, and pattern matching. It is crucial for JavaScript developers to understand how data structures work and how to design algorithms. This book and the accompanying code provide that essential foundation for doing so. With JavaScript Data Structures and Algorithms you can start developing your knowledge and applying it to your JavaScript projects today. Review core data structure funda ...
Hands-On Data Structures and Algorithms with Python, 3rd Edition
Hands-On Data Structures and Algorithms with Python, 3rd Edition

Choosing the right data structure is pivotal to optimizing the performance and scalability of applications. This new edition of Hands-On Data Structures and Algorithms with Python will expand your understanding of key structures, including stacks, queues, and lists, and also show you how to apply priority queues and heaps in applications. You'll learn how to analyze and compare Python algorithms, and understand which algorithms should be used for a problem based on running time and computational complexity. You will also become confident organizing your code in a manageable, consistent, and scalable way, which will boost your productivity as a Python developer. By the end of this Python book, you'll be able to manipulate the most important data structures and algorithms to more efficiently store, organize, and access data in your applications. ...
Apache Spark 2: Data Processing and Real-Time Analytics
Apache Spark 2: Data Processing and Real-Time Analytics

Apache Spark is an in-memory, cluster-based data processing system that provides a wide range of functionalities such as big data processing, analytics, machine learning, and more. With this Learning Path, you can take your knowledge of Apache Spark to the next level by learning how to expand Spark's functionality and building your own data flow and machine learning programs on this platform. You will work with the different modules in Apache Spark, such as interactive querying with Spark SQL, using DataFrames and datasets, implementing streaming analytics with Spark Streaming, and applying machine learning and deep learning techniques on Spark using MLlib and various external tools. By the end of this elaborately designed Learning Path, you will have all the knowledge you need to master Apache Spark, and build your own big data processing and analytics pipeline quickly and without any hassle. ...
Practical Python Data Wrangling and Data Quality
Practical Python Data Wrangling and Data Quality

The world around us is full of data that holds unique insights and valuable stories, and this book will help you uncover them. Whether you already work with data or want to learn more about its possibilities, the examples and techniques in this practical book will help you more easily clean, evaluate, and analyze data so that you can generate meaningful insights and compelling visualizations. Complementing foundational concepts with expert advice, author Susan E. McGregor provides the resources you need to extract, evaluate, and analyze a wide variety of data sources and formats, along with the tools to communicate your findings effectively. This book delivers a methodical, jargon-free way for data practitioners at any level, from true novices to seasoned professionals, to harness the power of data. Use Python 3.8+ to read, write, and transform data from a variety of sources; Understand and use programming basics in Python to wrangle data at scale; Organize, document, and structu ...
Enterprise Data Workflows with Cascading
Enterprise Data Workflows with Cascading

There is an easier way to build Hadoop applications. With this hands-on book, you'll learn how to use Cascading, the open source abstraction framework for Hadoop that lets you easily create and manage powerful enterprise-grade data processing applications - without having to learn the intricacies of MapReduce. Working with sample apps based on Java and other JVM languages, you'll quickly learn Cascading's streamlined approach to data processing, data filtering, and workflow optimization. This book demonstrates how this framework can help your business extract meaningful information from large amounts of distributed data. ...
Making Sense of Data I, 2nd Edition
Making Sense of Data I, 2nd Edition

A proven go-to guide for data analysis, Making Sense of Data I: A Practical Guide to Exploratory Data Analysis and Data Mining, Second Edition focuses on basic data analysis approaches that are necessary to make timely and accurate decisions in a diverse range of projects. Based on the authors' practical experience in implementing data analysis and data mining, the new edition provides clear explanations that guide readers from almost every field of study. In order to facilitate the needed steps when handling a data analysis or data mining project, a step-by-step approach aids professionals in carefully analyzing data and implementing results, leading to the development of smarter business decisions. ...
Big Data, Data Mining, and Machine Learning
Big Data, Data Mining, and Machine Learning

Big data is big business. But having the data and the computational power to process it isn't nearly enough to produce meaningful results. Big Data, Data Mining, and Machine Learning: Value Creation for Business Leaders and Practitioners is a complete resource for technology and marketing executives looking to cut through the hype and produce real results that hit the bottom line. Providing an engaging, thorough overview of the current state of big data analytics and the growing trend toward high performance computing architectures, the book is a detail-driven look into how big data analytics can be leveraged to foster positive change and drive efficiency. ...
Data Science for Business
Data Science for Business

Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today. Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You'll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company's data science projects. ...
Pervasive Computing and Networking
Pervasive Computing and Networking

This book presents state-of-the-art research on architectures, algorithms, protocols and applications in pervasive computing and networks. With the widespread availability of wireless and mobile networking technologies and the expected convergence of ubiquitous computing with these emerging technologies in the near future, pervasive computing and networking research and applications are among the hot topics on the agenda of researchers working on the next generation of mobile communications and networks. ...
Clojure Data Structures and Algorithms Cookbook
Clojure Data Structures and Algorithms Cookbook

Data-structures and algorithms often cross your path when you compress files, compile programs, access databases, or simply use your favourite text editor. Understanding and implementing them can be daunting. Curious learners and industrial developers can find these complex, especially if they focus on the detailed implementation of these data structures. Clojure is a highly pragmatic and expressive language with efficient and easy data manipulation capabilities. As such, it is great for implementing these algorithms. By abstracting away a great share of the unnecessary complexity resulting from implementation, Clojure and its contrib libraries will help you address various algorithmic challenges, making your data exploration both profitable and enjoyable. Through 25 recipes, you'll explore advanced algorithms and data-structures, well served by a sound Clojure implementation. ...
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