Programowanie

The Ultimate Docker Container Book. Build, ship, deploy, and scale containerized applications with Docker, Kubernetes, and the cloud - Fourth Edition

Dr. Gabriel N. Schenker

Containers have become the foundation of modern software platforms, transforming how applications are built, shipped, secured, and operated. However, as systems grow more distributed and regulated, using containers effectively requires more than basic commands, it requires architectural understanding, security awareness, and operational discipline.The Ultimate Docker Container Book, 4th edition takes you from container fundamentals to running production-grade platforms. Starting from first principles, the book explains how containers reduce friction in the software supply chain and progressively introduces images, networking, state management, testing, and debugging. You will learn how to design and operate distributed applications, manage multi-service systems, and apply orchestration using Kubernetes. This 4th edition places a stronger emphasis on security, governance, and compliance, reflecting real-world enterprise requirements. It also explores AI and automation in DevOps, showing how modern teams can enhance delivery and operations responsibly.Whether you are a developer, DevOps or platform engineer, or software architect, this book equips you with the skills and understanding needed to build secure, scalable, and future-ready container platforms.

The Ultimate Docker Container Book. Build, test, ship, and run containers with Docker and Kubernetes - Third Edition

Dr. Gabriel N. Schenker

The Ultimate Docker Container Book, 3rd edition enables you to leverage Docker containers for streamlined software development. You’ll uncover Docker fundamentals and how containers improve software supply chain efficiency and enhance security.You’ll start by learning practical skills such as setting up Docker environments, handling stateful components, running and testing code within containers, and managing Docker images. You’ll also explore how to adapt legacy applications for containerization and understand distributed application architecture. Next, you’ll delve into Docker's networking model, software-defined networks for secure applications, and Docker compose for managing multi-service applications along with tools for log analysis and metrics. You’ll further deepen your understanding of popular orchestrators like Kubernetes and Docker swarmkit, exploring their key concepts, and deployment strategies for resilient applications. In the final sections, you’ll gain insights into deploying containerized applications on major cloud platforms, including Azure, AWS, and GCE and discover techniques for production monitoring and troubleshooting.By the end of this book, you’ll be well-equipped to manage and scale containerized applications effectively.

The Unsupervised Learning Workshop. Get started with unsupervised learning algorithms and simplify your unorganized data to help make future predictions

Aaron Jones, Christopher Kruger, Benjamin Johnston

Do you find it difficult to understand how popular companies like WhatsApp and Amazon find valuable insights from large amounts of unorganized data? The Unsupervised Learning Workshop will give you the confidence to deal with cluttered and unlabeled datasets, using unsupervised algorithms in an easy and interactive manner.The book starts by introducing the most popular clustering algorithms of unsupervised learning. You'll find out how hierarchical clustering differs from k-means, along with understanding how to apply DBSCAN to highly complex and noisy data. Moving ahead, you'll use autoencoders for efficient data encoding.As you progress, you’ll use t-SNE models to extract high-dimensional information into a lower dimension for better visualization, in addition to working with topic modeling for implementing natural language processing (NLP). In later chapters, you’ll find key relationships between customers and businesses using Market Basket Analysis, before going on to use Hotspot Analysis for estimating the population density of an area.By the end of this book, you’ll be equipped with the skills you need to apply unsupervised algorithms on cluttered datasets to find useful patterns and insights.

Time Series Analysis on AWS. Learn how to build forecasting models and detect anomalies in your time series data

Michaël Hoarau

Being a business analyst and data scientist, you have to use many algorithms and approaches to prepare, process, and build ML-based applications by leveraging time series data, but you face common problems, such as not knowing which algorithm to choose or how to combine and interpret them. Amazon Web Services (AWS) provides numerous services to help you build applications fueled by artificial intelligence (AI) capabilities. This book helps you get to grips with three AWS AI/ML-managed services to enable you to deliver your desired business outcomes.The book begins with Amazon Forecast, where you’ll discover how to use time series forecasting, leveraging sophisticated statistical and machine learning algorithms to deliver business outcomes accurately. You’ll then learn to use Amazon Lookout for Equipment to build multivariate time series anomaly detection models geared toward industrial equipment and understand how it provides valuable insights to reinforce teams focused on predictive maintenance and predictive quality use cases. In the last chapters, you’ll explore Amazon Lookout for Metrics, and automatically detect and diagnose outliers in your business and operational data.By the end of this AWS book, you’ll have understood how to use the three AWS AI services effectively to perform time series analysis.

Time Series Analysis with Python Cookbook. Practical recipes for exploratory data analysis, data preparation, forecasting, and model evaluation

Tarek A. Atwan

Time series data is everywhere, available at a high frequency and volume. It is complex and can contain noise, irregularities, and multiple patterns, making it crucial to be well-versed with the techniques covered in this book for data preparation, analysis, and forecasting.This book covers practical techniques for working with time series data, starting with ingesting time series data from various sources and formats, whether in private cloud storage, relational databases, non-relational databases, or specialized time series databases such as InfluxDB. Next, you’ll learn strategies for handling missing data, dealing with time zones and custom business days, and detecting anomalies using intuitive statistical methods, followed by more advanced unsupervised ML models. The book will also explore forecasting using classical statistical models such as Holt-Winters, SARIMA, and VAR. The recipes will present practical techniques for handling non-stationary data, using power transforms, ACF and PACF plots, and decomposing time series data with multiple seasonal patterns. Later, you’ll work with ML and DL models using TensorFlow and PyTorch.Finally, you’ll learn how to evaluate, compare, optimize models, and more using the recipes covered in the book.

Time Series Analysis with Python Cookbook. Practical recipes for the complete time series workflow, from modern data engineering to advanced forecasting and anomaly detection - Second Edition

Tarek A. Atwan

To use time series data to your advantage, you need to master data preparation, analysis, and forecasting. This fully refreshed second edition helps you unlock insights from time series data with new chapters on probabilistic models, signal processing techniques, and new content on transformers. You’ll work with the latest releases of popular libraries like Pandas, Polars, Sktime, stats models, stats forecast, Darts, and Prophet through up-to-date examples.You'll hit the ground running by ingesting time series data from various sources and formats and learn strategies for handling missing data, dealing with time zones and custom business days, and detecting anomalies using intuitive statistical methods.Through detailed instructions, you'll explore forecasting using classical statistical models such as Holt-Winters, SARIMA, and VAR, and learn practical techniques for handling non-stationary data using power transforms, ACF and PACF plots, and decomposing time series data with seasonal patterns. The recipes then level up to cover more advanced topics such as building ML and DL models using TensorFlow and PyTorch and applying probabilistic modeling techniques. In this part, you’ll also be able to evaluate, compare, and optimize models, finishing with a strong command of wrangling data with Python.

Time Series Analysis with Spark. A practical guide to processing, modeling, and forecasting time series with Apache Spark

Yoni Ramaswami, Dael Williamson, Jan Govaere

Written by Databricks Senior Solutions Architect Yoni Ramaswami, whose expertise in Data and AI has shaped innovative digital transformations across industries, this comprehensive guide bridges foundational concepts of time series analysis with the Spark framework and Databricks, preparing you to tackle real-world challenges with confidence.From preparing and processing large-scale time series datasets to building reliable models, this book offers practical techniques that scale effortlessly for big data environments. You’ll explore advanced topics such as scaling your analyses, deploying time series models into production, Generative AI, and leveraging Spark's latest features for cutting-edge applications across industries. Packed with hands-on examples and industry-relevant use cases, this guide is perfect for data engineers, ML engineers, data scientists, and analysts looking to enhance their expertise in handling large-scale time series data.By the end of this book, you’ll have mastered the skills to design and deploy robust, scalable time series models tailored to your unique project needs—qualifying you to excel in the rapidly evolving world of big data analytics.*Email sign-up and proof of purchase required

Tkinter GUI Application Development Blueprints. Build nine projects by working with widgets, geometry management, event handling, and more - Second Edition

Bhaskar Chaudhary

Tkinter is the built-in GUI package that comes with standard Python distributions. It is a cross-platform package, which means you build once and deploy everywhere. It is simple to use and intuitive in nature, making it suitable for programmers and non-programmers alike.This book will help you master the art of GUI programming. It delivers the bigger picture of GUI programming by building real-world, productive, and fun applications such as a text editor, drum machine, game of chess, audio player, drawing application, piano tutor, chat application, screen saver, port scanner, and much more. In every project, you will build on the skills acquired in the previous project and gain more expertise. You will learn to write multithreaded programs, network programs, database-driven programs, asyncio based programming and more. You will also get to know the modern best practices involved in writing GUI apps. With its rich source of sample code, you can build upon the knowledge gained with this book and use it in your own projects in the discipline of your choice.