Scala: Applied Machine Learning. Master the art of Machine Learning in Scala

Patrick R. Nicolas, Alex Kozlov, Pascal Bugnion

This Learning Path aims to put the entire world of machine learning with Scala in front of you. Scala for Data Science, the first module in this course, is a tutorial guide that provides tutorials on some of the most common Scala libraries for data science, allowing you to quickly get up to speed building data science and data engineering solutions.The second course, Scala for Machine Learning guides you through the process of building AI applications with diagrams, formal mathematical notation, source code snippets, and useful tips. A review of the Akka framework and Apache Spark clusters concludes the tutorial.The next module, Mastering Scala Machine Learning, is the final step in this course. It will take your knowledge to next level and help you use the knowledge to build advanced applications such as social media mining, intelligent news portals, and more. After a quick refresher on functional programming concepts using REPL, you will see some practical examples of setting up the development environment and tinkering with data. We will then explore working with Spark and MLlib using k-means and decision trees.By the end of this course, you will be a master at Scala machine learning and have enough expertise to be able to build complex machine learning projects using Scala.This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products:? Scala for Data Science, Pascal Bugnion? Scala for Machine Learning, Patrick Nicolas? Mastering Scala Machine Learning, Alex Kozlov

Scala Data Analysis Cookbook. Navigate the world of data analysis, visualization, and machine learning with over 100 hands-on Scala recipes

Arun Manivannan

This book will introduce you to the most popular Scala tools, libraries, and frameworks through practical recipes around loading, manipulating, and preparing your data. It will also help you explore and make sense of your data using stunning and insightfulvisualizations, and machine learning toolkits.Starting with introductory recipes on utilizing the Breeze and Spark libraries, get to grips withhow to import data from a host of possible sources and how to pre-process numerical, string, and date data. Next, you’ll get an understanding of concepts that will help you visualize data using the Apache Zeppelin and Bokeh bindings in Scala, enabling exploratory data analysis. iscover how to program quintessential machine learning algorithms using Spark ML library. Work through steps to scale your machine learning models and deploy them into a standalone cluster, EC2, YARN, and Mesos. Finally dip into the powerful options presented by Spark Streaming, and machine learning for streaming data, as well as utilizing Spark GraphX.

Scala Design Patterns. Design modular, clean, and scalable applications by applying proven design patterns in Scala - Second Edition

Ivan Nikolov

Design patterns make developers’ lives easier by helping them write great software that is easy to maintain, runs efficiently, and is valuable to the company or people concerned. You’ll learn about the various features of Scala and will be able to apply well-known, industry-proven design patterns in your work. The book starts off by focusing on some of the most interesting and latest features of Scala while using practical real-world examples. We will be learning about IDE’s and Aspect Oriented Programming. We will be looking into different components in Scala. We will also cover the popular Gang of Four design patterns and show you how to incorporate functional patterns effectively. The book ends with a practical example that demonstrates how the presented material can be combined in real-life applications. You’ll learn the necessary concepts to build enterprise-grade applications. By the end of this book, you’ll have enough knowledge and understanding to quickly assess problems and come up with elegant solutions.

Scala Design Patterns. Write efficient, clean, and reusable code with Scala

Ivan Nikolov

Scala has become increasingly popular in many different IT sectors. The language is exceptionally feature-rich which helps developers write less code and get faster results. Design patterns make developer’s lives easier by helping them write great software that is easy to maintain, runs efficiently and is valuable to the company or people concerned.You will learn about the various features of Scala and be able to apply well-known, industry-proven design patterns in your work. The book starts off by focusing on some of the most interesting features of Scala while using practical real-world examples. We will also cover the popular Gang of Four design patterns and show you how to incorporate functional patterns effectively. By the end of this book, you will have enough knowledge and understanding to quickly assess problems and come up with elegant solutions.

Scala for Data Science. Leverage the power of Scala with different tools to build scalable, robust data science applications

Pascal Bugnion

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.

Scala for Java Developers. Build reactive, scalable applications and integrate Java code with the power of Scala

Thomas Alexandre

Scala for Machine Learning. Build systems for data processing, machine learning, and deep learning - Second Edition

Patrick R. Nicolas

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 Naïve 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.

Scala for Machine Learning. Leverage Scala and Machine Learning to construct and study systems that can learn from data

Patrick R. Nicolas

Scala Functional Programming Patterns. Grok and perform effective functional programming in Scala

Atul S. Khot

Scala is used to construct elegant class hierarchies for maximum code reuse and extensibility and to implement their behavior using higher-order functions. Its functional programming (FP) features are a boon to help you design “easy to reason about” systems to control the growing software complexities. Knowing how and where to apply the many Scala techniques is challenging. Looking at Scala best practices in the context of what you already know helps you grasp these concepts quickly, and helps you see where and why to use them. This book begins with the rationale behind patterns to help you understand where and why each pattern is applied. You will discover what tail recursion brings to your table and will get an understanding of how to create solutions without mutations. We then explain the concept of memorization and infinite sequences for on-demand computation. Further, the book takes you through Scala’s stackable traits and dependency injection, a popular technique to produce loosely-coupled software systems.You will also explore how to currying favors to your code and how to simplify it by de-construction via pattern matching. We also show you how to do pipeline transformations using higher order functions such as the pipes and filters pattern. Then we guide you through the increasing importance of concurrent programming and the pitfalls of traditional code concurrency. Lastly, the book takes a paradigm shift to show you the different techniques that functional programming brings to your plate.This book is an invaluable source to help you understand and perform functional programming and solve common programming problems using Scala’s programming patterns.

Scala: Guide for Data Science Professionals. Build robust data pipelines with Scala

Arun Manivannan, Pascal Bugnion, Patrick R. Nicolas

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, Naïve 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

Scala Machine Learning Projects. Build real-world machine learning and deep learning projects with Scala

Md. Rezaul Karim

Machine learning has had a huge impact on academia and industry by turning data into actionable information. Scala has seen a steady rise in adoption over the past few years, especially in the fields of data science and analytics. This book is for data scientists, data engineers, and deep learning enthusiasts who have a background in complex numerical computing and want to know more hands-on machine learning application development.If you're well versed in machine learning concepts and want to expand your knowledge by delving into the practical implementation of these concepts using the power of Scala, then this book is what you need! Through 11 end-to-end projects, you will be acquainted with popular machine learning libraries such as Spark ML, H2O, DeepLearning4j, and MXNet.At the end, you will be able to use numerical computing and functional programming to carry out complex numerical tasks to develop, build, and deploy research or commercial projects in a production-ready environment.

Scala. Nauka programowania

Vikash Sharma

Scala jest językiem programowania ogólnego przeznaczenia, który łączy cechy języków funkcyjnych i obiektowych. Jego twórcy postawili sobie za cel skalowalność napisanych w nim aplikacji - stąd wzięła się nazwa Scala. Scala jest oparta na wirtualnej maszynie Javy, umożliwia programowanie funkcyjne i oferuje bogaty wybór typów. Dzięki tym cechom można tworzyć kod mniej podatny na występowanie błędów w trakcie działania programu. Po uzyskaniu pewnej biegłości w kodowaniu praca z tym językiem staje się prawdziwą przyjemnością, nawet podczas tworzenia frameworków czy bibliotek. Ten przystępny podręcznik przeznaczono dla programistów, którzy chcą poznać język Scala, aby wykorzystywać go do pisania współbieżnych, skalowalnych i reaktywnych aplikacji. Przedstawiono tu podstawy niezbędne do rozpoczęcia kodowania w Scali: składnię języka, podstawowe typy danych, literały czy zmienne. Następnie omówiono struktury danych w Scali i sposoby korzystania z funkcji wyższego rzędu. Zaprezentowano również takie koncepcje jak dopasowanie wzorca, klasy przypadku oraz zagadnienia związane z programowaniem funkcyjnym i programowaniem zorientowanym obiektowo. Opisano techniki programowania asynchronicznego i reaktywnego. Znalazło się tu także obszerne wprowadzenie do frameworka Akka. W tej książce między innymi: paradygmaty programowania a korzystanie ze Scali kolekcje modyfikowalne i niemodyfikowalne koncepcja domniemania i praca z wyjątkami programowanie równoległe, asynchroniczne i reaktywne programowanie sterowane testami w Scali Scala: nowoczesność i prostota w każdej skali!

Scala od podszewki

Joshua Suereth D.

Scala to słowo, które ostatnio nie schodzi z ust programistów Javy. Pod tą nazwą kryje się język łączący światy programowania funkcyjnego i obiektowego. Jego ogromną zaletą jest działanie w oparciu o wirtualną maszynę Javy. Pozwala to między innymi na bezproblemową komunikację i współdzielenie kodu między oboma językami. James Gosling, twórca Javy, zapytany o to, jakiego języka oprogramowania działającego w ten sposób użyłby obecnie (gdyby nie mógł wykorzystać Javy), odparł bez zastanowienia: „Scala!”. To chyba najlepszy dowód na to, że ten język wart jest Twojego czasu! Dzięki tej książce opanujesz Scalę szybko i bezboleśnie, więc będziesz mógł wykorzystać jej zalety już w najbliższym projekcie. W trakcie lektury poznasz składnię, fundamentalne zasady tworzenia oprogramowania w Scali oraz konwencje kodowania w tym języku. W kolejnych rozdziałach dowiesz się, czym są niejawne widoki, jakie typy danych masz do dyspozycji i jakie są ich ograniczenia. Co jeszcze? Integracja Scali z Javą to niezwykle istotny temat, dający Ci pole do popisu! Ponadto poznasz wzorce stosowane w programowaniu funkcyjnym. Słowo wstępne do tej niezwykłej książki napisał sam Martin Odersky - twórca języka Scala! Niniejsza książka jest najlepszym kompendium wiedzy na temat programowania w tym języku. Musisz ją mieć! Poznaj: konwencje obowiązujące w Scali składnię języka najlepsze wzorce projektowe stosowane w programowaniu funkcyjnym potencjał języka Scala! Poznaj i wykorzystaj potęgę programowania funkcyjnego!

Scala Programming Projects. Build real-world projects using popular Scala frameworks such as Play, Akka, and Spark

Mikael Valot, Nicolas Jorand

Scala Programming Projects is a comprehensive project-based introduction for those who are new to Scala. Complete with step-by-step instructions and easy-to-follow tutorials that demonstrate best practices when building applications, this Scala book will have you building real-world projects in no time.Starting with the fundamentals of software development, you’ll begin with simple projects, such as developing a financial independence calculator, and then advance to more complex projects, such as a building a shopping application and a Bitcoin transaction analyzer. You’ll explore a variety of Scala features, including its OOP and FP capabilities, and learn how to write concise, reactive, and concurrent applications in a type-safe manner. You’ll also understand how to use libraries such as Akka and Play. Furthermore, you’ll be able to integrate your Scala apps with Kafka, Spark, and Zeppelin, along with deploying applications on a cloud platform.By the end of the book, you’ll have a firm foundation in Java programming that’ll enable you to solve a variety of real-world problems, and you’ll have built impressive projects to add to your professional portfolio.

Scala Reactive Programming. Build scalable, functional reactive microservices with Akka, Play, and Lagom

Rambabu Posa

Reactive programming is a scalable, fast way to build applications, and one that helps us write code that is concise, clear, and readable. It can be used for many purposes such as GUIs, robotics, music, and others, and is central to many concurrent systems. This book will be your guide to getting started with Reactive programming in Scala.You will begin with the fundamental concepts of Reactive programming and gradually move on to working with asynchronous data streams. You will then start building an application using Akka Actors and extend it using the Play framework. You will also learn about reactive stream specifications, event sourcing techniques, and different methods to integrate Akka Streams into the Play Framework. This book will also take you one step forward by showing you the advantages of the Lagom framework while working with reactive microservices. You will also learn to scale applications using multi-node clusters and test, secure, and deploy your microservices to the cloud.By the end of the book, you will have gained the knowledge to build robust and distributed systems with Scala and Akka.

Scala Test-Driven Development. Write clean scala code that works

Gaurav Sood

Test-driven development (TDD) produces high-quality applications in less time than is possible with traditional methods. Due to the systematic nature of TDD, the application is tested in individual units as well as cumulatively, right from the design stage, to ensure optimum performance and reduced debugging costs. This step-by-step guide shows you how to use the principles of TDD and built-in Scala testing modules to write clean and fully tested Scala code and give your workflow the change it needs to let you create better applications than ever before. After an introduction to TDD, you will learn the basics of ScalaTest, one of the most flexible and most popular testing tools around for Scala, by building your first fully test-driven application. Building on from that you will learn about the ScalaTest API and how to refactor code to produce high-quality applications. We’ll teach you the concepts of BDD (Behavior-driven development) and you’ll see how to add functional tests to the existing suite of tests. You’ll be introduced to the concepts of Mocks and Stubs and will learn to increase test coverage using properties. With a concluding chapter on miscellaneous tools, this book will enable you to write better quality code that is easily maintainable and watch your apps change for the better.

Scalable Application Development with NestJS. Leverage REST, GraphQL, microservices, testing, and deployment for seamless growth

Pacifique Linjanja

In this book, Pacifique Linjanja, a globally recognized software engineer and open-source contributor, shares his deep technical expertise and practical insights from his extensive experience delivering enterprise-level applications to unpack the full potential of NestJS, the cutting-edge Node.js framework.This book covers the core concepts, design patterns, and best practices for building scalable, high-performance applications with NestJS. You’ll learn REST API and GraphQL implementations, harness the power of microservices, and explore real-world case studies, including e-commerce, social networking, and ERP systems. The chapters provide step-by-step guidance for setting up your development environment with TypeScript and npm, structuring projects effectively, and using the Apollo Federation architecture to create efficient GraphQL APIs. This book offers hands-on guidance for testing and debugging APIs, handling exceptions, and validating data using pipes and guards, all while helping you build a complete NestJS application from scratch.By the end, you'll be ready to apply DevOps principles for continuous integration and deployment, as well as secure your NestJS applications using advanced techniques.

Scalable Data Analytics with Azure Data Explorer. Modern ways to query, analyze, and perform real-time data analysis on large volumes of data

Jason Myerscough, Arunee Singhchawla

Azure Data Explorer (ADX) enables developers and data scientists to make data-driven business decisions. This book will help you rapidly explore and query your data at scale and secure your ADX clusters.The book begins by introducing you to ADX, its architecture, core features, and benefits. You'll learn how to securely deploy ADX instances and navigate through the ADX Web UI, cover data ingestion, and discover how to query and visualize your data using the powerful Kusto Query Language (KQL). Next, you'll get to grips with KQL operators and functions to efficiently query and explore your data, as well as perform time series analysis and search for anomalies and trends in your data. As you progress through the chapters, you'll explore advanced ADX topics, including deploying your ADX instances using Infrastructure as Code (IaC). The book also shows you how to manage your cluster performance and monthly ADX costs by handling cluster scaling and data retention periods. Finally, you'll understand how to secure your ADX environment by restricting access with best practices for improving your KQL query performance.By the end of this Azure book, you'll be able to securely deploy your own ADX instance, ingest data from multiple sources, rapidly query your data, and produce reports with KQL and Power BI.

Scalable Data Architecture with Java. Build efficient enterprise-grade data architecting solutions using Java

Sinchan Banerjee

Java architectural patterns and tools help architects to build reliable, scalable, and secure data engineering solutions that collect, manipulate, and publish data.This book will help you make the most of the architecting data solutions available with clear and actionable advice from an expert.You’ll start with an overview of data architecture, exploring responsibilities of a Java data architect, and learning about various data formats, data storage, databases, and data application platforms as well as how to choose them. Next, you’ll understand how to architect a batch and real-time data processing pipeline. You’ll also get to grips with the various Java data processing patterns, before progressing to data security and governance. The later chapters will show you how to publish Data as a Service and how you can architect it. Finally, you’ll focus on how to evaluate and recommend an architecture by developing performance benchmarks, estimations, and various decision metrics.By the end of this book, you’ll be able to successfully orchestrate data architecture solutions using Java and related technologies as well as to evaluate and present the most suitable solution to your clients.

Scalable Data Streaming with Amazon Kinesis. Design and secure highly available, cost-effective data streaming applications with Amazon Kinesis

Tarik Makota, Brian Maguire, Danny Gagne, Rajeev Chakrabarti

Amazon Kinesis is a collection of secure, serverless, durable, and highly available purpose-built data streaming services. This data streaming service provides APIs and client SDKs that enable you to produce and consume data at scale.Scalable Data Streaming with Amazon Kinesis begins with a quick overview of the core concepts of data streams, along with the essentials of the AWS Kinesis landscape. You'll then explore the requirements of the use case shown through the book to help you get started and cover the key pain points encountered in the data stream life cycle. As you advance, you'll get to grips with the architectural components of Kinesis, understand how they are configured to build data pipelines, and delve into the applications that connect to them for consumption and processing. You'll also build a Kinesis data pipeline from scratch and learn how to implement and apply practical solutions. Moving on, you'll learn how to configure Kinesis on a cloud platform. Finally, you’ll learn how other AWS services can be integrated into Kinesis. These services include Redshift, Dynamo Database, AWS S3, Elastic Search, and third-party applications such as Splunk.By the end of this AWS book, you’ll be able to build and deploy your own Kinesis data pipelines with Kinesis Data Streams (KDS), Kinesis Data Firehose (KFH), Kinesis Video Streams (KVS), and Kinesis Data Analytics (KDA).

Scales of Banach Spaces, Theory of Interpolation and their Applications

Łukasz Dawidowski

Celem niniejszej monografii jest omówienie teorii skal przestrzeni Banacha oraz teorii interpolacji wraz z podaniem przykładów ich zastosowań. W pierwszej kolejności opisano teoretyczne podstawy teorii interpolacji. Podano  definicje oraz podstawowe twierdzenia dotyczące konstrukcji przestrzeni interpolacyjnych (interpolacja rzeczywista i zespolona). Druga, główna, część monografii przedstawia definicję potęg ułamkowych operatorów, w szczególności dodatnich operatorów sektorialnych. Zaprezentowano także ich zastosowanie do konstrukcji skal przestrzeni Banacha, które jako główny obiekt badań są przykładem przestrzeni interpolacyjnych. W pracy zamieszczono również charakteryzację skal przestrzeni Banacha, która służy jako podstawa teoretyczna do opisu zastosowań tej teorii. W trzeciej części pokazano wykorzystanie podanej wcześniej teorii do badania „zachowań” operatorów na różnych poziomach skali. Udowodniono twierdzenia dotyczące operatorów domkniętych oraz operatorów sektorialnych. Następnie opisano konkretne równania cząstkowe, w rozwiązywaniu których można zastosować wspomnianą teorię.

Scaling Agile with Jira Align. A practical guide to strategically scaling agile across teams, programs, and portfolios in enterprises

Dean MacNeil, Aslam Cader

Jira Align is a platform purpose-built for enterprises to connect strategy with execution and drive transparency, consistency, and predictability at all levels of scale. The platform supports business value delivery in agile frameworks such as LeSS, DAD, and SAFe. It also caters to organizations that mix agile with waterfall to support scaled bimodal delivery.Starting with an introduction to the platform and its features, this book takes you through the foundational building blocks of Jira Align. You’ll learn how an organization can benefit from implementing Jira Align and understand how to connect dimensions such as people, work, time, and outcomes. The book takes you through the typical steps for implementing Jira Align for maximizing outcomes and helps you solve common team, program, and portfolio-level challenges by enhancing visibility, tracking dependencies and risks, and using reports for real-time, distributed decision making. Throughout the book, you’ll explore features such as remote agile ceremonies, live roadmaps, and objectives and key results (OKRs). You’ll also get to grips with lean portfolio management, financial reporting, and using the program board for planning and execution.By the end of this book, you’ll be well versed in the key features of Jira Align and be able to leverage them to support all levels of agile at scale.

Scaling Apache Solr. Optimize your searches using high-performance enterprise search repositories with Apache Solr

Hrishikesh Vijay Karambelkar

Scaling Big Data with Hadoop and Solr. Understand, design, build, and optimize your big data search engine with Hadoop and Apache Solr

Hrishikesh Vijay Karambelkar