Verleger: K-i-s-publishing
Tom Sluiter, Dmitry Anoshin
SAP on Azure Implementation Guide. Move your business data to the cloud
Nick Morgan, Bartosz Jarkowski
Cloud technologies have now reached a level where even the most critical business systems can run on them. For most organizations SAP is the key business system. If SAP is unavailable for any reason then potentially your business stops. Because of this, it is understandable that you will be concerned whether such a critical system can run in the public cloud. However, the days when you truly ran your IT system on-premises have long since gone. Most organizations have been getting rid of their own data centers and increasingly moving to co-location facilities. In this context the public cloud is nothing more than an additional virtual data center connected to your existing network.There are typically two main reasons why you may consider migrating SAP to Azure: You need to replace the infrastructure that is currently running SAP, or you want to migrate SAP to a new database. Depending on your goal SAP offers different migration paths. You can decide either to migrate the current workload to Azure as-is, or to combine it with changing the database and execute both activities as a single step. SAP on Azure Implementation Guide covers the main migration options to lead you through migrating your SAP data to Azure simply and successfully.
Harish Gulati
SAS is a groundbreaking tool for advanced predictive and statistical analytics used by top banks and financial corporations to establish insights from their financial data.SAS for Finance offers you the opportunity to leverage the power of SAS analytics in redefining your data. Packed with real-world examples from leading financial institutions, the author discusses statistical models using time series data to resolve business issues.This book shows you how to exploit the capabilities of this high-powered package to create clean, accurate financial models. You can easily assess the pros and cons of models to suit your unique business needs.By the end of this book, you will be able to leverage the true power of SAS to design and develop accurate analytical models to gain deeper insights into your financial data.
Bass Jobsen
Sass and Compass Designer's Cookbook helps you to get most out of CSS3 and harness its benefits to create engaging and receptive applications. This book will help you develop faster and reduce the maintenance time for your web development projects by using Sass and Compass. You will learn how to use with CSS frameworks such as Bootstrap and Foundation and understand how to use other libraries of pre-built mixins. You will also learn setting up a development environment with Gulp. This book guides you through all the concepts and gives you practical examples for full understanding.
Md. Rezaul Karim, Sridhar Alla
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.
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
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.
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.
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.
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 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
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.
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.
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.
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.*Email sign-up and proof of purchase required
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.
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.