The second edition of Bayesian Analysis with Python is an introduction to the main concepts of applied Bayesian inference and its practical implementation in Python using PyMC3, a state-of-the-art probabilistic programming library, and ArviZ, a new library for exploratory analysis of Bayesian models. The main concepts of Bayesian statistics are covered using a practical and computational approach. Synthetic and real data sets are used to introduce several types of models, such as generalized linear models for regression and classification, mixture models, hierarchical models, and Gaussian processes, among others. By the end of the book, you will have a working knowledge of probabilistic modeling and you will be able to design and implement Bayesian models for your own data science problems. After reading the book you will be better prepared to delve into more advanced material or specialized statistical modeling if you need to.

Deep learning is a branch of machine learning based on a set of algorithms that attempt to model high-level abstractions in data. Advanced Deep Learning with R will help you understand popular deep learning architectures and their variants in R, along with providing real-life examples for them.

Building enterprise-grade distributed applications and executing systematic search operations call for a strong understanding of Elasticsearch and expertise in using its core APIs and latest features. This book will help you master the advanced functionalities of Elasticsearch and understand how you can develop a sophisticated, real-time search engine confidently. In addition to this, you'll also learn to run machine learning jobs in Elasticsearch to speed up routine tasks.

Over the past few years, Continuous Delivery (CD) and DevOps have been in the spotlight in tech media, at conferences, and in boardrooms alike. Many articles and books have been written covering the technical aspects of CD and DevOps, yet the vast majority of the industry doesn’t fully understand what they actually are and how, if adopted correctly they can help organizations drastically change the way they deliver value. This book will help you figure out how CD and DevOps can help you to optimize, streamline, and improve the way you work to consistently deliver quality software.

«UPgrade» – периодический журнал о компьютерах и компьютерных технологиях, который стал первопроходцем на рынке массовых изданий о высоких технологиях. Сегодня издание – признанный лидер в своем медиасегменте. UPgrade – первое издание для широкого круга читателей, которых интересует не только сам по себе апгрейд компьютера, но и все, что так или иначе связано с миром IT.

Data in the genomics field is booming. In just a few years, organizations such as the National Institutes of Health (NIH) will host 50+ petabytes—or over 50 million gigabytes—of genomic data, and they’re turning to cloud infrastructure to make that data available to the research community. How do you adapt analysis tools and protocols to access and analyze that volume of data in the cloud? With this practical book, researchers will learn how to work with genomics algorithms using open source tools including the Genome Analysis Toolkit (GATK), Docker, WDL, and Terra. Geraldine Van der Auwera, longtime custodian of the GATK user community, and Brian O’Connor of the UC Santa Cruz Genomics Institute, guide you through the process. You’ll learn by working with real data and genomics algorithms from the field.

Take full creative control of your web applications with Flask, the Python-based microframework. With the second edition of this hands-on book, you’ll learn the framework from the ground up by developing, step-by-step, a real-world project created by author Miguel Grinberg. This refreshed edition accounts for important technology changes that have occurred in the past three years. You’ll learn the framework’s core functionality, as well as how to extend applications with advanced web techniques such as database migration and web service communication. The first part of each chapter provides you with reference and background for the topic in question, while the second part guides you though a hands-on implementation of the topic. If you have Python experience, this book shows you how to take advantage of the creative freedom Flask provides.

With so much data being continuously generated, developers, who can present data as impactful and interesting visualizations, are always in demand. Interactive Data Visualization with Python sharpens your data exploration skills, tells you everything there is to know about interactive data visualization in Python. You'll begin by learning how to draw various plots with Matplotlib and Seaborn, the non-interactive data visualization libraries. You'll study different types of visualizations, compare them, and find out how to select a particular type of visualization to suit your requirements.

If you’re new to Java—or new to programming—this best-selling book will guide you through the language features and APIs of Java 11. With fun, compelling, and realistic examples, authors Marc Loy, Patrick Niemeyer, and Daniel Leuck introduce you to Java fundamentals—including its class libraries, programming techniques, and idioms—with an eye toward building real applications.

Эта книга идеально подходит как для начинающих программистов, так и для тех, кто только собирается осваивать Python, но уже имеет опыт программирования на других языках. В ней подробно рассматриваются самые современные пакеты и библиотеки Python. Стилистически издание напоминает руководство с вкраплениями кода, подробно объясняя различные концепции Python 3. Под обложкой вы найдете обширный материал от самых основ языка до сравнительно сложных и узких тем. Прочитав эту книгу, вы не только убедитесь, что Python – это вкусно, но и освоите искусство тестирования, отладки, многократного использования кода, а также научитесь применять Python в различных предметных областях.