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Book Scientific Computing with Scala

Download or read book Scientific Computing with Scala written by Vytautas Jancauskas and published by Packt Publishing Ltd. This book was released on 2016-04-27 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn to solve scientific computing problems using Scala and its numerical computing, data processing, concurrency, and plotting libraries About This Book Parallelize your numerical computing code using convenient and safe techniques. Accomplish common high-performance, scientific computing goals in Scala. Learn about data visualization and how to create high-quality scientific plots in Scala Who This Book Is For Scientists and engineers who would like to use Scala for their scientific and numerical computing needs. A basic familiarity with undergraduate level mathematics and statistics is expected but not strictly required. A basic knowledge of Scala is required as well as the ability to write simple Scala programs. However, complicated programming concepts are not used in the book. Anyone who wants to explore using Scala for writing scientific or engineering software will benefit from the book. What You Will Learn Write and read a variety of popular file formats used to store scientific data Use Breeze for linear algebra, optimization, and digital signal processing Gain insight into Saddle for data analysis Use ScalaLab for interactive computing Quickly and conveniently write safe parallel applications using Scala's parallel collections Implement and deploy concurrent programs using the Akka framework Use the Wisp plotting library to produce scientific plots Visualize multivariate data using various visualization techniques In Detail Scala is a statically typed, Java Virtual Machine (JVM)-based language with strong support for functional programming. There exist libraries for Scala that cover a range of common scientific computing tasks – from linear algebra and numerical algorithms to convenient and safe parallelization to powerful plotting facilities. Learning to use these to perform common scientific tasks will allow you to write programs that are both fast and easy to write and maintain. We will start by discussing the advantages of using Scala over other scientific computing platforms. You will discover Scala packages that provide the functionality you have come to expect when writing scientific software. We will explore using Scala's Breeze library for linear algebra, optimization, and signal processing. We will then proceed to the Saddle library for data analysis. If you have experience in R or with Python's popular pandas library you will learn how to translate those skills to Saddle. If you are new to data analysis, you will learn basic concepts of Saddle as well. Well will explore the numerical computing environment called ScalaLab. It comes bundled with a lot of scientific software readily available. We will use it for interactive computing, data analysis, and visualization. In the following chapters, we will explore using Scala's powerful parallel collections for safe and convenient parallel programming. Topics such as the Akka concurrency framework will be covered. Finally, you will learn about multivariate data visualization and how to produce professional-looking plots in Scala easily. After reading the book, you should have more than enough information on how to start using Scala as your scientific computing platform Style and approach Examples are provided on how to use Scala to do basic numerical and scientific computing tasks. All the concepts are illustrated with more involved examples in each chapter. The goal of the book is to allow you to translate existing experience in scientific computing to Scala.

Book Scala  Guide for Data Science Professionals

Download or read book Scala Guide for Data Science Professionals written by Pascal Bugnion and published by . This book was released on 2017 with total page 1101 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Introduction to the Art of Programming Using Scala

Download or read book Introduction to the Art of Programming Using Scala written by Mark C. Lewis and published by CRC Press. This book was released on 2012-11-05 with total page 938 pages. Available in PDF, EPUB and Kindle. Book excerpt: With its flexibility for programming both small and large projects, Scala is an ideal language for teaching beginning programming. Yet there are no textbooks on Scala currently available for the CS1/CS2 levels. Introduction to the Art of Programming Using Scala presents many concepts from CS1 and CS2 using a modern, JVM-based language that works we

Book Scala for Machine Learning

Download or read book Scala for Machine Learning written by Patrick R. Nicolas and published by Packt Publishing Ltd. This book was released on 2017-09-26 with total page 740 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage Scala and Machine Learning to study and construct systems that can learn from data About This Book Explore a broad variety of data processing, machine learning, and genetic algorithms through diagrams, mathematical formulation, and updated source code in Scala Take your expertise in Scala programming to the next level by creating and customizing AI applications Experiment with different techniques and evaluate their benefits and limitations using real-world applications in a tutorial style Who This Book Is For If you're a data scientist or a data analyst with a fundamental knowledge of Scala who wants to learn and implement various Machine learning techniques, this book is for you. All you need is a good understanding of the Scala programming language, a basic knowledge of statistics, a keen interest in Big Data processing, and this book! What You Will Learn Build dynamic workflows for scientific computing Leverage open source libraries to extract patterns from time series Write your own classification, clustering, or evolutionary algorithm Perform relative performance tuning and evaluation of Spark Master probabilistic models for sequential data Experiment with advanced techniques such as regularization and kernelization Dive into neural networks and some deep learning architecture Apply some basic multiarm-bandit algorithms Solve big data problems with Scala parallel collections, Akka actors, and Apache Spark clusters Apply key learning strategies to a technical analysis of financial markets In Detail The discovery of information through data clustering and classification is becoming a key differentiator for competitive organizations. Machine learning applications are everywhere, from self-driving cars, engineering design, logistics, manufacturing, and trading strategies, to detection of genetic anomalies. The book is your one stop guide that introduces you to the functional capabilities of the Scala programming language that are critical to the creation of machine learning algorithms such as dependency injection and implicits. You start by learning data preprocessing and filtering techniques. Following this, you'll move on to unsupervised learning techniques such as clustering and dimension reduction, followed by probabilistic graphical models such as Naive Bayes, hidden Markov models and Monte Carlo inference. Further, it covers the discriminative algorithms such as linear, logistic regression with regularization, kernelization, support vector machines, neural networks, and deep learning. You'll move on to evolutionary computing, multibandit algorithms, and reinforcement learning. Finally, the book includes a comprehensive overview of parallel computing in Scala and Akka followed by a description of Apache Spark and its ML library. With updated codes based on the latest version of Scala and comprehensive examples, this book will ensure that you have more than just a solid fundamental knowledge in machine learning with Scala. Style and approach This book is designed as a tutorial with hands-on exercises using technical analysis of financial markets and corporate data. The approach of each chapter is such that it allows you to understand key concepts easily.

Book Functional Programming in Scala

Download or read book Functional Programming in Scala written by Paul Chiusano and published by Simon and Schuster. This book was released on 2014-09-01 with total page 457 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Functional Programming in Scala is a serious tutorial for programmers looking to learn FP and apply it to the everyday business of coding. The book guides readers from basic techniques to advanced topics in a logical, concise, and clear progression. In it, you'll find concrete examples and exercises that open up the world of functional programming. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Functional programming (FP) is a style of software development emphasizing functions that don't depend on program state. Functional code is easier to test and reuse, simpler to parallelize, and less prone to bugs than other code. Scala is an emerging JVM language that offers strong support for FP. Its familiar syntax and transparent interoperability with Java make Scala a great place to start learning FP. About the Book Functional Programming in Scala is a serious tutorial for programmers looking to learn FP and apply it to their everyday work. The book guides readers from basic techniques to advanced topics in a logical, concise, and clear progression. In it, you'll find concrete examples and exercises that open up the world of functional programming. This book assumes no prior experience with functional programming. Some prior exposure to Scala or Java is helpful. What's Inside Functional programming concepts The whys and hows of FP How to write multicore programs Exercises and checks for understanding About the Authors Paul Chiusano and Rúnar Bjarnason are recognized experts in functional programming with Scala and are core contributors to the Scalaz library. Table of Contents PART 1 INTRODUCTION TO FUNCTIONAL PROGRAMMING What is functional programming? Getting started with functional programming in Scala Functional data structures Handling errors without exceptions Strictness and laziness Purely functional state PART 2 FUNCTIONAL DESIGN AND COMBINATOR LIBRARIES Purely functional parallelism Property-based testing Parser combinators PART 3 COMMON STRUCTURES IN FUNCTIONAL DESIGN Monoids Monads Applicative and traversable functors PART 4 EFFECTS AND I/O External effects and I/O Local effects and mutable state Stream processing and incremental I/O

Book Introduction to Programming and Problem Solving Using Scala

Download or read book Introduction to Programming and Problem Solving Using Scala written by Mark C. Lewis and published by CRC Press. This book was released on 2016-10-14 with total page 591 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the first edition: "The well-written, comprehensive book...[is] aiming to become a de facto reference for the language and its features and capabilities. The pace is appropriate for beginners; programming concepts are introduced progressively through a range of examples and then used as tools for building applications in various domains, including sophisticated data structures and algorithms...Highly recommended. Students of all levels, faculty, and professionals/practitioners.—D. Papamichail, University of Miami in CHOICE Magazine Mark Lewis’ Introduction to the Art of Programming Using Scala was the first textbook to use Scala for introductory CS courses. Fully revised and expanded, the new edition of this popular text has been divided into two books. Introduction to Programming and Problem-Solving Using Scala is designed to be used in first semester college classrooms to teach students beginning programming with Scala. The book focuses on the key topics students need to know in an introductory course, while also highlighting the features that make Scala a great programming language to learn. The book is filled with end-of-chapter projects and exercises, and the authors have also posted a number of different supplements on the book website. Video lectures for each chapter in the book are also available on YouTube. The videos show construction of code from the ground up and this type of "live coding" is invaluable for learning to program, as it allows students into the mind of a more experienced programmer, where they can see the thought processes associated with the development of the code. About the Authors Mark Lewis is a Professor at Trinity University. He teaches a number of different courses, spanning from first semester introductory courses to advanced seminars. His research interests included simulations and modeling, programming languages, and numerical modeling of rings around planets with nearby moons. Lisa Lacher is an Assistant Professor at the University of Houston, Clear Lake with over 25 years of professional software development experience. She teaches a number of different courses spanning from first semester introductory courses to graduate level courses. Her research interests include Computer Science Education, Agile Software Development, Human Computer Interaction and Usability Engineering, as well as Measurement and Empirical Software Engineering.

Book Scala for Machine Learning  Second Edition

Download or read book Scala for Machine Learning Second Edition written by Patrick R. Nicolas and published by Packt Publishing. This book was released on 2017-09-26 with total page 740 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage Scala and Machine Learning to study and construct systems that can learn from dataAbout This Book* Explore a broad variety of data processing, machine learning, and genetic algorithms through diagrams, mathematical formulation, and updated source code in Scala* Take your expertise in Scala programming to the next level by creating and customizing AI applications* Experiment with different techniques and evaluate their benefits and limitations using real-world applications in a tutorial styleWho This Book Is ForIf you're a data scientist or a data analyst with a fundamental knowledge of Scala who wants to learn and implement various Machine learning techniques, this book is for you. All you need is a good understanding of the Scala programming language, a basic knowledge of statistics, a keen interest in Big Data processing, and this book!What You Will Learn* Build dynamic workflows for scientific computing* Leverage open source libraries to extract patterns from time series* Write your own classification, clustering, or evolutionary algorithm* Perform relative performance tuning and evaluation of Spark* Master probabilistic models for sequential data* Experiment with advanced techniques such as regularization and kernelization* Dive into neural networks and some deep learning architecture* Apply some basic multiarm-bandit algorithms* Solve big data problems with Scala parallel collections, Akka actors, and Apache Spark clusters* Apply key learning strategies to a technical analysis of financial marketsIn DetailThe discovery of information through data clustering and classification is becoming a key differentiator for competitive organizations. Machine learning applications are everywhere, from self-driving cars, engineering design, logistics, manufacturing, and trading strategies, to detection of genetic anomalies.The book is your one stop guide that introduces you to the functional capabilities of the Scala programming language that are critical to the creation of machine learning algorithms such as dependency injection and implicits. You start by learning data preprocessing and filtering techniques. Following this, you'll move on to unsupervised learning techniques such as clustering and dimension reduction, followed by probabilistic graphical models such as Naive Bayes, hidden Markov models and Monte Carlo inference. Further, it covers the discriminative algorithms such as linear, logistic regression with regularization, kernelization, support vector machines, neural networks, and deep learning. You'll move on to evolutionary computing, multibandit algorithms, and reinforcement learning.Finally, the book includes a comprehensive overview of parallel computing in Scala and Akka followed by a description of Apache Spark and its ML library. With updated codes based on the latest version of Scala and comprehensive examples, this book will ensure that you have more than just a solid fundamental knowledge in machine learning with Scala.Style and approachThis book is designed as a tutorial with hands-on exercises using technical analysis of financial markets and corporate data. The approach of each chapter is such that it allows you to understand key concepts easily.

Book Object Orientation  Abstraction  and Data Structures Using Scala

Download or read book Object Orientation Abstraction and Data Structures Using Scala written by Mark C. Lewis and published by CRC Press. This book was released on 2017-01-06 with total page 662 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the first edition: "The well-written, comprehensive book...[is] aiming to become a de facto reference for the language and its features and capabilities. The pace is appropriate for beginners; programming concepts are introduced progressively through a range of examples and then used as tools for building applications in various domains, including sophisticated data structures and algorithms...Highly recommended. Students of all levels, faculty, and professionals/practitioners. —D. Papamichail, University of Miami in CHOICE Magazine Mark Lewis’ Introduction to the Art of Programming Using Scala was the first textbook to use Scala for introductory CS courses. Fully revised and expanded, the new edition of this popular text has been divided into two books. Object-Orientation, Abstraction, and Data Structures Using Scala, Second Edition is intended to be used as a textbook for a second or third semester course in Computer Science. The Scala programming language provides powerful constructs for expressing both object orientation and abstraction. This book provides students with these tools of object orientation to help them structure solutions to larger, more complex problems, and to expand on their knowledge of abstraction so that they can make their code more powerful and flexible. The book also illustrates key concepts through the creation of data structures, showing how data structures can be written, and the strengths and weaknesses of each one. Libraries that provide the functionality needed to do real programming are also explored in the text, including GUIs, multithreading, and networking. The book is filled with end-of-chapter projects and exercises, and the authors have also posted a number of different supplements on the book website. Video lectures for each chapter in the book are also available on YouTube. The videos show construction of code from the ground up and this type of "live coding" is invaluable for learning to program, as it allows students into the mind of a more experienced programmer, where they can see the thought processes associated with the development of the code. About the Authors Mark Lewis is an Associate Professor at Trinity University. He teaches a number of different courses, spanning from first semester introductory courses to advanced seminars. His research interests included simulations and modeling, programming languages, and numerical modeling of rings around planets with nearby moons. Lisa Lacher is an Assistant Professor at the University of Houston, Clear Lake with over 25 years of professional software development experience. She teaches a number of different courses spanning from first semester introductory courses to graduate level courses. Her research interests include Computer Science Education, Agile Software Development, Human Computer Interaction and Usability Engineering, as well as Measurement and Empirical Software Engineering.

Book Modern Systems Programming with Scala Native

Download or read book Modern Systems Programming with Scala Native written by Richard Whaling and published by Pragmatic Bookshelf. This book was released on 2020-01-23 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: Access the power of bare-metal systems programming with Scala Native, an ahead-of-time Scala compiler. Without the baggage of legacy frameworks and virtual machines, Scala Native lets you re-imagine how your programs interact with your operating system. Compile Scala code down to native machine instructions; seamlessly invoke operating system APIs for low-level networking and IO; control pointers, arrays, and other memory management techniques for extreme performance; and enjoy instant start-up times. Skip the JVM and improve your code performance by getting close to the metal. Developers generally build systems on top of the work of those who came before, accumulating layer upon layer of abstraction. Scala Native provides a rare opportunity to remove layers. Without the JVM, Scala Native uses POSIX and ANSI C APIs to build concise, expressive programs that run unusually close to bare metal. Scala Native compiles Scala code down to native machine instructions instead of JVM bytecode. It starts up fast, without the sluggish warm-up phase that's common for just-in-time compilers. Scala Native programs can seamlessly invoke operating system APIs for low-level networking and IO. And Scala Native lets you control pointers, arrays, and other memory layout types for extreme performance. Write practical, bare-metal code with Scala Native, step by step. Understand the foundations of systems programming, including pointers, arrays, strings, and memory management. Use the UNIX socket API to write network client and server programs without the sort of frameworks higher-level languages rely on. Put all the pieces together to design and implement a modern, asynchronous microservice-style HTTP framework from scratch. Take advantage of Scala Native's clean, modern syntax to write lean, high-performance code without the JVM. What You Need: A modern Windows, Mac OS, or Linux system capable of running Docker. All code examples in the book are designed to run on a portable Docker-based build environment that runs anywhere. If you don't have Docker yet, see the Appendix for instructions on how to get it.

Book Data Structures and Algorithms with Scala

Download or read book Data Structures and Algorithms with Scala written by Bhim P. Upadhyaya and published by Springer. This book was released on 2019-02-26 with total page 154 pages. Available in PDF, EPUB and Kindle. Book excerpt: This practically-focused textbook presents a concise tutorial on data structures and algorithms using the object-functional language Scala. The material builds upon the foundation established in the title Programming with Scala: Language Exploration by the same author, which can be treated as a companion text for those less familiar with Scala. Topics and features: discusses data structures and algorithms in the form of design patterns; covers key topics on arrays, lists, stacks, queues, hash tables, binary trees, sorting, searching, and graphs; describes examples of complete and running applications for each topic; presents a functional approach to implementations for data structures and algorithms (excepting arrays); provides numerous challenge exercises (with solutions), encouraging the reader to take existing solutions and improve upon them; offers insights from the author’s extensive industrial experience; includes a glossary, and an appendix supplying an overview of discrete mathematics. Highlighting the techniques and skills necessary to quickly derive solutions to applied problems, this accessible text will prove invaluable to time-pressured students and professional software engineers.

Book Object Orientation  Abstraction  and Data Structures Using Scala  Second Edition

Download or read book Object Orientation Abstraction and Data Structures Using Scala Second Edition written by Mark C. Lewis and published by CRC Press. This book was released on 2017-01-06 with total page 805 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the first edition: "The well-written, comprehensive book...[is] aiming to become a de facto reference for the language and its features and capabilities. The pace is appropriate for beginners; programming concepts are introduced progressively through a range of examples and then used as tools for building applications in various domains, including sophisticated data structures and algorithms...Highly recommended. Students of all levels, faculty, and professionals/practitioners.? —D. Papamichail, University of Miami in CHOICE Magazine ? Mark Lewis’ Introduction to the Art of Programming Using Scala?was the first textbook to use Scala for introductory CS courses. Fully revised and expanded, the new edition of this popular text has been divided into two books. Object-Orientation, Abstraction, and Data Structures Using Scala, Second Edition is intended to be used as a textbook for a second or third semester course in Computer Science. The Scala programming language provides powerful constructs for expressing both object orientation and abstraction. This book provides students with these tools of object orientation to help them structure solutions to larger, more complex problems, and to expand on their knowledge of abstraction so that they can make their code more powerful and flexible. The book also illustrates key concepts through the creation of data structures, showing how data structures can be written, and the strengths and weaknesses of each one. Libraries that provide the functionality needed to do real programming are also explored in the text, including GUIs, multithreading, and networking. The book is filled with end-of-chapter projects and exercises, and the authors have also posted a number of different supplements on the book website. Video lectures for each chapter in the book are also available on YouTube. The videos show construction of code from the ground up and this type of "live coding" is invaluable for learning to program, as it allows students into the mind of a more experienced programmer, where they can see the thought processes associated with the development of the code. About the Authors Mark Lewis is an Associate Professor at Trinity University. He teaches a number of different courses, spanning from first semester introductory courses to advanced seminars. His research interests included simulations and modeling, programming languages, and numerical modeling of rings around planets with nearby moons.? Lisa Lacher is an Assistant Professor at the University of Houston, Clear Lake with over 25 years of professional software development experience. She teaches a number of different courses spanning from first semester introductory courses to graduate level courses. Her research interests include Computer Science Education, Agile Software Development, Human Computer Interaction and Usability Engineering, as well as Measurement and Empirical Software Engineering.

Book Scala and Spark for Big Data Analytics

Download or read book Scala and Spark for Big Data Analytics written by Md. Rezaul Karim and published by Packt Publishing Ltd. This book was released on 2017-07-25 with total page 786 pages. Available in PDF, EPUB and Kindle. Book excerpt: Harness the power of Scala to program Spark and analyze tonnes of data in the blink of an eye! About This Book Learn Scala's sophisticated type system that combines Functional Programming and object-oriented concepts Work on a wide array of applications, from simple batch jobs to stream processing and machine learning Explore the most common as well as some complex use-cases to perform large-scale data analysis with Spark Who This Book Is For Anyone who wishes to learn how to perform data analysis by harnessing the power of Spark will find this book extremely useful. No knowledge of Spark or Scala is assumed, although prior programming experience (especially with other JVM languages) will be useful to pick up concepts quicker. What You Will Learn Understand object-oriented & functional programming concepts of Scala In-depth understanding of Scala collection APIs Work with RDD and DataFrame to learn Spark's core abstractions Analysing structured and unstructured data using SparkSQL and GraphX Scalable and fault-tolerant streaming application development using Spark structured streaming Learn machine-learning best practices for classification, regression, dimensionality reduction, and recommendation system to build predictive models with widely used algorithms in Spark MLlib & ML Build clustering models to cluster a vast amount of data Understand tuning, debugging, and monitoring Spark applications Deploy Spark applications on real clusters in Standalone, Mesos, and YARN In Detail Scala has been observing wide adoption over the past few years, especially in the field of data science and analytics. Spark, built on Scala, has gained a lot of recognition and is being used widely in productions. Thus, if you want to leverage the power of Scala and Spark to make sense of big data, this book is for you. The first part introduces you to Scala, helping you understand the object-oriented and functional programming concepts needed for Spark application development. It then moves on to Spark to cover the basic abstractions using RDD and DataFrame. This will help you develop scalable and fault-tolerant streaming applications by analyzing structured and unstructured data using SparkSQL, GraphX, and Spark structured streaming. Finally, the book moves on to some advanced topics, such as monitoring, configuration, debugging, testing, and deployment. You will also learn how to develop Spark applications using SparkR and PySpark APIs, interactive data analytics using Zeppelin, and in-memory data processing with Alluxio. By the end of this book, you will have a thorough understanding of Spark, and you will be able to perform full-stack data analytics with a feel that no amount of data is too big. Style and approach Filled with practical examples and use cases, this book will hot only help you get up and running with Spark, but will also take you farther down the road to becoming a data scientist.

Book Hands on Scala Programming  Learn Scala in a Practical  Project Based Way

Download or read book Hands on Scala Programming Learn Scala in a Practical Project Based Way written by Haoyi Li and published by . This book was released on 2020-07-11 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hands-on Scala teaches you how to use the Scala programming language in a practical, project-based fashion. This book is designed to quickly teach an existing programmer everything needed to go from "hello world" to building production applications like interactive websites, parallel web crawlers, and distributed systems in Scala. In the process you will learn how to use the Scala language to solve challenging problems in an elegant and intuitive manner.

Book Scala  Guide for Data Science Professionals

Download or read book Scala Guide for Data Science Professionals written by Pascal Bugnion and published by Packt Publishing Ltd. This book was released on 2017-02-24 with total page 1101 pages. Available in PDF, EPUB and Kindle. Book excerpt: Scala will be a valuable tool to have on hand during your data science journey for everything from data cleaning to cutting-edge machine learning About This Book Build data science and data engineering solutions with ease An in-depth look at each stage of the data analysis process — from reading and collecting data to distributed analytics Explore a broad variety of data processing, machine learning, and genetic algorithms through diagrams, mathematical formulations, and source code Who This Book Is For This learning path is perfect for those who are comfortable with Scala programming and now want to enter the field of data science. Some knowledge of statistics is expected. What You Will Learn Transfer and filter tabular data to extract features for machine learning Read, clean, transform, and write data to both SQL and NoSQL databases Create Scala web applications that couple with JavaScript libraries such as D3 to create compelling interactive visualizations Load data from HDFS and HIVE with ease Run streaming and graph analytics in Spark for exploratory analysis Bundle and scale up Spark jobs by deploying them into a variety of cluster managers Build dynamic workflows for scientific computing Leverage open source libraries to extract patterns from time series Master probabilistic models for sequential data In Detail Scala is especially good for analyzing large sets of data as the scale of the task doesn't have any significant impact on performance. Scala's powerful functional libraries can interact with databases and build scalable frameworks — resulting in the creation of robust data pipelines. The first module introduces you to Scala libraries to ingest, store, manipulate, process, and visualize data. Using real world examples, you will learn how to design scalable architecture to process and model data — starting from simple concurrency constructs and progressing to actor systems and Apache Spark. After this, you will also learn how to build interactive visualizations with web frameworks. Once you have become familiar with all the tasks involved in data science, you will explore data analytics with Scala in the second module. You'll see how Scala can be used to make sense of data through easy to follow recipes. You will learn about Bokeh bindings for exploratory data analysis and quintessential machine learning with algorithms with Spark ML library. You'll get a sufficient understanding of Spark streaming, machine learning for streaming data, and Spark graphX. Armed with a firm understanding of data analysis, you will be ready to explore the most cutting-edge aspect of data science — machine learning. The final module teaches you the A to Z of machine learning with Scala. You'll explore Scala for dependency injections and implicits, which are used to write machine learning algorithms. You'll also explore machine learning topics such as clustering, dimentionality reduction, Naive Bayes, Regression models, SVMs, neural networks, and more. This learning path combines some of the best that Packt has to offer into one complete, curated package. It includes content from the following Packt products: Scala for Data Science, Pascal Bugnion Scala Data Analysis Cookbook, Arun Manivannan Scala for Machine Learning, Patrick R. Nicolas Style and approach A complete package with all the information necessary to start building useful data engineering and data science solutions straight away. It contains a diverse set of recipes that cover the full spectrum of interesting data analysis tasks and will help you revolutionize your data analysis skills using Scala.

Book Programming Scala

    Book Details:
  • Author : Dean Wampler
  • Publisher : "O'Reilly Media, Inc."
  • Release : 2014-12-04
  • ISBN : 1491950153
  • Pages : 498 pages

Download or read book Programming Scala written by Dean Wampler and published by "O'Reilly Media, Inc.". This book was released on 2014-12-04 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get up to speed on Scala, the JVM language that offers all the benefits of a modern object model, functional programming, and an advanced type system. Packed with code examples, this comprehensive book shows you how to be productive with the language and ecosystem right away, and explains why Scala is ideal for today's highly scalable, data-centric applications that support concurrency and distribution. This second edition covers recent language features, with new chapters on pattern matching, comprehensions, and advanced functional programming. You’ll also learn about Scala’s command-line tools, third-party tools, libraries, and language-aware plugins for editors and IDEs. This book is ideal for beginning and advanced Scala developers alike. Program faster with Scala’s succinct and flexible syntax Dive into basic and advanced functional programming (FP) techniques Build killer big-data apps, using Scala’s functional combinators Use traits for mixin composition and pattern matching for data extraction Learn the sophisticated type system that combines FP and object-oriented programming concepts Explore Scala-specific concurrency tools, including Akka Understand how to develop rich domain-specific languages Learn good design techniques for building scalable and robust Scala applications

Book Scala for Data Science

    Book Details:
  • Author : Pascal Bugnion
  • Publisher : Packt Publishing Ltd
  • Release : 2016-01-28
  • ISBN : 1785289381
  • Pages : 416 pages

Download or read book Scala for Data Science written by Pascal Bugnion and published by Packt Publishing Ltd. This book was released on 2016-01-28 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage the power of Scala with different tools to build scalable, robust data science applications About This Book A complete guide for scalable data science solutions, from data ingestion to data visualization Deploy horizontally scalable data processing pipelines and take advantage of web frameworks to build engaging visualizations Build functional, type-safe routines to interact with relational and NoSQL databases with the help of tutorials and examples provided Who This Book Is For If you are a Scala developer or data scientist, or if you want to enter the field of data science, then this book will give you all the tools you need to implement data science solutions. What You Will Learn Transform and filter tabular data to extract features for machine learning Implement your own algorithms or take advantage of MLLib's extensive suite of models to build distributed machine learning pipelines Read, transform, and write data to both SQL and NoSQL databases in a functional manner Write robust routines to query web APIs Read data from web APIs such as the GitHub or Twitter API Use Scala to interact with MongoDB, which offers high performance and helps to store large data sets with uncertain query requirements Create Scala web applications that couple with JavaScript libraries such as D3 to create compelling interactive visualizations Deploy scalable parallel applications using Apache Spark, loading data from HDFS or Hive In Detail Scala is a multi-paradigm programming language (it supports both object-oriented and functional programming) and scripting language used to build applications for the JVM. Languages such as R, Python, Java, and so on are mostly used for data science. It is particularly good at analyzing large sets of data without any significant impact on performance and thus Scala is being adopted by many developers and data scientists. Data scientists might be aware that building applications that are truly scalable is hard. Scala, with its powerful functional libraries for interacting with databases and building scalable frameworks will give you the tools to construct robust data pipelines. This book will introduce you to the libraries for ingesting, storing, manipulating, processing, and visualizing data in Scala. Packed with real-world examples and interesting data sets, this book will teach you to ingest data from flat files and web APIs and store it in a SQL or NoSQL database. It will show you how to design scalable architectures to process and modelling your data, starting from simple concurrency constructs such as parallel collections and futures, through to actor systems and Apache Spark. As well as Scala's emphasis on functional structures and immutability, you will learn how to use the right parallel construct for the job at hand, minimizing development time without compromising scalability. Finally, you will learn how to build beautiful interactive visualizations using web frameworks. This book gives tutorials on some of the most common Scala libraries for data science, allowing you to quickly get up to speed with building data science and data engineering solutions. Style and approach A tutorial with complete examples, this book will give you the tools to start building useful data engineering and data science solutions straightaway

Book Scala High Performance Programming

Download or read book Scala High Performance Programming written by Vincent Theron and published by Packt Publishing. This book was released on 2016-05-31 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: Write efficient, clean, and powerful Scala code and create high-performing applications that your users will loveAbout This Book*This is the first book that explores Scala performance techniques in depth, including how to benchmark your performance so you can understand where to make gains*It provides a first-principles examination of what performance means in a Scala context*This book was written by industry experts Vincent Theron and Michael DiamantWho This Book Is ForIf you are a Scala developer with experience in programming Scala applications and know the basics in Scala, syntax, and frameworks such as Lift or Play, this book is for you. This book will also be useful if you are a Java developer who is interested in switching to Scala, but you don't want to give up the performance of Java code. No knowledge of anything outside Scala is required.What You Will Learn*Find out about performance and how to evaluate the behavior of an application*Analyze the performance of your application on JVM*Use Scala features to achieve a high performance benchmark for your application*Enhance the performance of your application with the Collection API*Explore asynchronous programming to achieve concurrency and parallelism*Achieve a deeper understanding of high performance using advanced toolsIn DetailScala is a statically and strongly typed language that tries to elegantly blend both functional and object-oriented paradigms. It has experienced growing popularity in the past few years as both an appealing and pragmatic choice to write production-ready software in the functional paradigm. Scala lets you solve problems with less code than the alternatives. However, this programmatic gain can come at the cost of performance if you aren't careful.Scala High Performance Programming is written to arm you with the knowledge you need to create highly efficient, clean Scala applications. Starting with the basics of understanding what performance is in a Scala context, we'll look at how to benchmark your performance so you can see the results of your optimizations in action. We'?ll also take a deep dive into type specialization, concurrency, and parallel programming. By the end of the book, you'll be able to code efficient, optimized, solutions in Scala.