Informatyka

Sass i Compass. Praktyczny przewodnik dla projektantów

Ben Frain

Projektuj pięknie i wygodnie — Sass i Compass do Twoich usług! Instalowanie Sass i Compass oraz konfigurowanie projektów, czyli od czego zacząć naukę Kolory, siatki i responsywność, czyli jak zapewnić stronie dobry wygląd na każdym urządzeniu Automatyzacja pisania kodu CSS, czyli jak działać szybko i eliminować zbędne czynności Kaskadowe arkusze stylów są dziś wykorzystywane przez wszystkich projektantów stron internetowych na całym świecie. Jest to bardzo wygodne i elastyczne narzędzie, jednak prawdziwie spektakularne efekty można osiągnąć dzięki zastosowaniu CSS w połączeniu z preprocesorem Sass oraz technologią Compass. Możliwe, że nie bardzo wiesz, co znaczą te nazwy, i nie masz pojęcia, do czego mogłyby Ci się przydać te dodatki. Jeśli jednak jesteś projektantem, powinieneś czym prędzej zapoznać się z tymi narzędziami, ponieważ niebywale ułatwią Ci pracę. I nie musisz być geniuszem ani informatykiem, żeby skorzystać z ich mocy. Wystarczy, że znasz HTML i CSS. Ta książka nie została napisana z myślą o programistach. Jej celem jest pokazanie spektrum działania technologii Sass i Compass wszystkim tym, którzy często używają CSS. Znajdziesz tu informacje na temat instalowania i konfigurowania obu dodatków, sprawnego posługiwania się kolorami i tworzenia responsywnych układów stron. Po tych podstawach przyjdzie czas na naukę pisania zapytań medialnych i eksperymentalnych deklaracji CSS dla różnych przeglądarek, a także ćwiczenia ze sporządzania statystyk. Następnie dowiesz się, jak utworzyć idealnego duszka w rekordowo krótkim czasie i zautomatyzować swoją pracę za pomocą inteligentnych pętli. Przeczytaj i zastosuj, a szybko zakochasz się w dodatkach Sass i Compass! Sass i Compass dla początkujących Tworzenie projektu Sass i Compass Zagnieżdżanie, rozszerzanie, symbole zastępcze i domieszki Praca z kolorami Responsywne i elastyczne siatki Tworzenie zapytań medialnych za pomocą Sass i domieszek CSS3, duszki i inne cuda Logika programistyczna w Sass Sass i Compass dla zaawansowanych Sass i Compass skrócą Ci drogę do pięknych stron!

Scala and Spark for Big Data Analytics. Explore the concepts of functional programming, data streaming, and machine learning

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

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 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.