Sąsiadka boskiego Peruna

Justyna Kowalczyk

Jedna kobieta, dwóch słowiańskich bogów i tajemnicza przepowiednia. Róża wdaje się w romans ze swoim wrednym, ale bosko przystojnym sąsiadem, Piotrem. Nie wie, że mężczyzna to ludzkie wcielenie Peruna, słowiańskiego boga nieba, który wraz z innymi bóstwami został w pradawnych czasach skazany na życie na Ziemi. Piotr natychmiast rozpoznaje w Róży boginię Mokosz. Zgodnie z przepowiednią jej narodziny są początkiem powrotu starych słowiańskich bogów oraz krwawego konfliktu między nimi. Perun stanie do walki przeciwko własnemu bratu. To będzie bitwa o najwyższą stawkę... Różę. Czy w wojnie bogów życie i los dziewczyny mają jakieś znaczenie? Czy miłość boga może zmienić przeznaczenie?

Sąsiadka z trzeciego piętra

Eugenia Dalmau

Pozorny spokój panujący w budynku stojącym w eleganckiej dzielnicy Walencji zostaje zmącony nagłą śmiercią jednego z sąsiadów, Enriquego Ginera. Ignacio, psychiatra mieszkający na najwyższym piętrze, zauważa w noc śmierci sąsiada, że ktoś ukradł mu bloczek recept. Violeta, sąsiadka z trzeciego piętra, zaalarmowana dziwnymi wydarzeniami, zaczyna przyglądać się uważnie życiu mieszkańców budynku: wdowy próbującej po trupach osiągnąć swoje cele i jej samotnego czterdziestoczteroletniego syna; atrakcyjnego rozwodnika; kobiety zdominowanej i doprowadzonej do szaleństwa przez swojego perfidnego męża; idealnego małżeństwa, rodziców czworga idealnych dzieci, i antypatycznej wdowy po zamordowanym. Z pomocą Ignacia i bystrej dozorczyni Violeta odkryje, że nic nie jest tym, czym się wydaje, i powoli zagłębi się w plątaninę kłamstw, a jej śledztwo doprowadzi ją do momentu, kiedy zacznie się bać o własne życie. Eugenia Dalmau to hiszpańska autorka kryminałów, która urodziła się i studiowała w Walencji. Jak sama mówi, najbardziej niespodziewane miejsce albo wiadomość może sprawić, że wymyśla historię, a najbardziej absurdalne sytuacje pozwalają stworzyć bohatera. W swoich powieściach łączy suspens z codziennymi sytuacjami, bo czy istnieje coś bardziej intrygującego od samego życia? 

Sąsiedztwo

Ignacy Krasicki

Ignacy Krasicki Bajki i przypowieści Sąsiedztwo Zeszło żyto na ziemi leżącej odłogiem: Cóż po tym, kiedy zewsząd otoczone głogiem. Grunt był dobry, chociaż go pług nigdy nie ruszył; Byłoby z niego zboże głóg wszystko zagłuszył. Szczęśliwy, kto z równymi o granicę siedzi! Zły głód, wojna, powiet... Ignacy Krasicki Ur. 3 lutego 1735 r. w Dubiecku (Sanockie) Zm. 14 marca 1801 r. w Berlinie Najważniejsze dzieła: Myszeida (1775), Mikołaja Doświadczyńskiego przypadki (1776), Monachomachia (1778), Pan Podstoli (1778 i 1784), Bajki i przypowieści (1779), Satyry (1779 i 1782), Antymonachomachia (1779), Wojna chocimska (1780) Wybitny polski poeta, prozaik, komediopisarz i publicysta. Kasztelanic chełmski, hrabia, przeznaczony do stanu duchownego ze względu na trudną sytuację materialną rodziny. Od 1766 r. biskup warmiński. Blisko współpracował z królem Stanisławem Augustem w dziele kulturalnego ożywienia kraju. Tworzył w duchu oświecenia (m.in. napisał w latach 1781-83 dwutomową encyklopedię Zbiór potrzebniejszych wiadomości, był twórcą pierwszego pol. czasopisma, (Monitor), ale jego Hymn do miłości ojczyzny (1774) oraz przekład Pieśni Osjana odegrały znaczącą rolę w kształtowaniu polskiego romantyzmu. Kupując książkę wspierasz fundację Nowoczesna Polska, która propaguje ideę wolnej kultury. Wolne Lektury to biblioteka internetowa, rozwijana pod patronatem Ministerstwa Edukacji Narodowej. W jej zbiorach znajduje się kilka tysięcy utworów, w tym wiele lektur szkolnych zalecanych do użytku przez MEN, które trafiły już do domeny publicznej. Wszystkie dzieła są odpowiednio opracowane - opatrzone przypisami oraz motywami.

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 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!