Programowanie
Paola Annis, Giuliano Caglio
Cloud teams and ICT cost controllers working with Azure will be able to put their knowledge to work with this practical guide, introducing a process model for structured cost governance. The Road to Azure Cost Governance is a must-read if you find yourself facing the harsh reality of monthly cloud costs gradually getting out of control.Starting with how resources are created and managed, everything you need to know in order to track, display, optimize, rightsize, and clean up cloud resources will be tackled with a workflow approach that will leave the choice of operation to you (be it the Azure CLI, automation, logic apps, or even custom code). Using real-world datasets, you'll learn everything from basic cost management to modeling your cloud spend across your technical resources in a sustainable way. The book will also show you how to create a recursive optimization process that will give you full control of spending and savings, while helping you reserve budget for future cloud projects and innovation.By the end of this Azure book, you'll have a clear understanding and control of your cloud spend along with knowledge of a number of cost-saving techniques used by companies around the world, application optimization patterns, and the carbon impact of your cloud infrastructure.
Paola Annis, Giuliano Caglio
Cloud teams and ICT cost controllers working with Azure will be able to put their knowledge to work with this practical guide, introducing a process model for structured cost governance. The Road to Azure Cost Governance is a must-read if you find yourself facing the harsh reality of monthly cloud costs gradually getting out of control.Starting with how resources are created and managed, everything you need to know in order to track, display, optimize, rightsize, and clean up cloud resources will be tackled with a workflow approach that will leave the choice of operation to you (be it the Azure CLI, automation, logic apps, or even custom code). Using real-world datasets, you'll learn everything from basic cost management to modeling your cloud spend across your technical resources in a sustainable way. The book will also show you how to create a recursive optimization process that will give you full control of spending and savings, while helping you reserve budget for future cloud projects and innovation.By the end of this Azure book, you'll have a clear understanding and control of your cloud spend along with knowledge of a number of cost-saving techniques used by companies around the world, application optimization patterns, and the carbon impact of your cloud infrastructure.
Akshat Paul, Peter Philips, Dániel Szabó ,...
The beauty of Ruby is its readability and expressiveness. Ruby hides away a lot of the complexity of programming, allowing you to work quickly and 'do more' with fewer lines of code. This makes it a great programming language for beginners, but learning any new skill can still be a daunting task. If you want to learn to code using Ruby, but don't know where to start, The Ruby Workshop will help you cut through the noise and make sense of this fun, flexible language.You'll start by writing and running simple code snippets and Ruby source code files. After learning about strings, numbers, and booleans, you'll see how to store collections of objects with arrays and hashes. You'll then learn how to control the flow of a Ruby program using boolean logic.The book then delves into OOP and explains inheritance, encapsulation, and polymorphism. Gradually, you'll build your knowledge of advanced concepts by learning how to interact with external APIs, before finally exploring the most popular Ruby framework ? Ruby on Rails ? and using it for web development.Throughout this book, you'll work on a series of realistic projects, including simple games, a voting application, and an online blog. By the end of this Ruby book, you'll have the knowledge, skills and confidence to creatively tackle your own ambitious projects with Ruby.
The Rust Programming Handbook. An end-to-end guide to mastering Rust fundamentals
Francesco Ciulla
The Rust Programming Handbook is a deeply engaging and meticulously crafted book designed to immerse programmers into the intricate world of Rust’s core principles and sophisticated features. This book not only enhances your coding skills but also prepares you to tackle complex challenges in software development, optimizing your code for better performance and reliability.You will explore Rust’s powerful concurrency models, rigorous memory safety guarantees, and its versatile trait system. Discover the foundational elements that make Rust a standout language for developing safe and efficient applications. The book will show you how these core principles can seamlessly transition into real-world applications. You will learn how to apply Rust's capabilities to systems programming and web development, extending the reach of its safety and efficiency benefits across different programming domains. Whether it's creating low-level system components or high-performance web services, the book provides practical examples to integrate Rust effectively into a variety of projects.Elevate your coding skills and become a sought-after professional in the tech industry with this essential guide. Rust from Beginner to Professional is your definitive toolkit for mastering advanced Rust programming techniques and writing high-quality code.
The Rust Programming Handbook. An end-to-end guide to mastering Rust fundamentals
Francesco Ciulla
The Rust Programming Handbook is a deeply engaging and meticulously crafted book designed to immerse programmers into the intricate world of Rust’s core principles and sophisticated features. This book not only enhances your coding skills but also prepares you to tackle complex challenges in software development, optimizing your code for better performance and reliability.You will explore Rust’s powerful concurrency models, rigorous memory safety guarantees, and its versatile trait system. Discover the foundational elements that make Rust a standout language for developing safe and efficient applications. The book will show you how these core principles can seamlessly transition into real-world applications. You will learn how to apply Rust's capabilities to systems programming and web development, extending the reach of its safety and efficiency benefits across different programming domains. Whether it's creating low-level system components or high-performance web services, the book provides practical examples to integrate Rust effectively into a variety of projects.Elevate your coding skills and become a sought-after professional in the tech industry with this essential guide. Rust from Beginner to Professional is your definitive toolkit for mastering advanced Rust programming techniques and writing high-quality code.
Fred Heath
Curious why so many rely on Scrum and what makes Agile so effective? Learn from seasoned software engineer and Scrum expert Fred Heath, everything you need to become a certified Scrum Master. With over two decades of experience across the software development lifecycle, Fred brings invaluable insights from his extensive work in Scrum, both as a Scrum Master and developer. In this updated guide, he not only takes you from Scrum basics to mastery but also offers practical, real-world knowledge to help you become an effective Scrum Master.The first part of the book introduces the Scrum fundamentals and prepares you for Level I certification, covering the importance of Scrum team structure, the benefits of well-planned sprints, and how to create and manage sprint and product backlogs.The second part elevates your skills to the Level II certification standard, exploring advanced topics such as Scrum anti-patterns, scaling Scrum, and how to support developers and product owners. Each chapter concludes with quizzes to reinforce the concepts you've learned. The book wraps up with exam preparation tips and myth-busting strategies to give you a competitive edge in passing your Scrum Master exams.By the end of this book, you'll be proficient as a Scrum Master ensuring you won’t fall behind in an ever-increasingly agile world.
Dr. Logan Song, Yu Meng
As cloud computing continues to revolutionize IT, professionals face the challenge of keeping up with rapidly evolving technologies. This book provides a clear roadmap for mastering cloud concepts, developing hands-on expertise, and obtaining professional certifications, making it an essential resource for those looking to advance their careers in cloud computing.Starting with a focus on the Amazon cloud, you’ll be introduced to fundamental AWS cloud services, followed by advanced AWS cloud services in the domains of data, machine learning, and security. Next, you’ll build proficiency in Microsoft Azure cloud and Google Cloud Platform (GCP) by examining the common attributes of the three clouds, differentiating their unique features, along with leveraging real-life cloud project implementations on these cloud platforms. Through hands-on projects and real-world applications, you’ll gain the skills needed to work confidently across different cloud platforms. The book concludes with career development guidance, including certification paths and industry insights to help you succeed in the cloud computing landscape.Walking through this cloud computing book, you’ll systematically establish a robust footing in AWS, Azure, and GCP, and emerge as a cloud-savvy professional, equipped with cloud certificates to validate your skills.
Peter Farrell , Alvaro Fuentes , Ajinkya...
Are you looking to start developing artificial intelligence applications? Do you need a refresher on key mathematical concepts? Full of engaging practical exercises, The Statistics and Calculus with Python Workshop will show you how to apply your understanding of advanced mathematics in the context of Python.The book begins by giving you a high-level overview of the libraries you'll use while performing statistics with Python. As you progress, you'll perform various mathematical tasks using the Python programming language, such as solving algebraic functions with Python starting with basic functions, and then working through transformations and solving equations. Later chapters in the book will cover statistics and calculus concepts and how to use them to solve problems and gain useful insights. Finally, you'll study differential equations with an emphasis on numerical methods and learn about algorithms that directly calculate values of functions.By the end of this book, you’ll have learned how to apply essential statistics and calculus concepts to develop robust Python applications that solve business challenges.
Liu Peng
The Statistics and Machine Learning with R Workshop is a comprehensive resource packed with insights into statistics and machine learning, along with a deep dive into R libraries. The learning experience is further enhanced by practical examples and hands-on exercises that provide explanations of key concepts.Starting with the fundamentals, you’ll explore the complete model development process, covering everything from data pre-processing to model development. In addition to machine learning, you’ll also delve into R's statistical capabilities, learning to manipulate various data types and tackle complex mathematical challenges from algebra and calculus to probability and Bayesian statistics. You’ll discover linear regression techniques and more advanced statistical methodologies to hone your skills and advance your career.By the end of this book, you'll have a robust foundational understanding of statistics and machine learning. You’ll also be proficient in using R's extensive libraries for tasks such as data processing and model training and be well-equipped to leverage the full potential of R in your future projects.
Blaine Bateman, Ashish Ranjan Jha, Benjamin Johnston,...
Would you like to understand how and why machine learning techniques and data analytics are spearheading enterprises globally? From analyzing bioinformatics to predicting climate change, machine learning plays an increasingly pivotal role in our society.Although the real-world applications may seem complex, this book simplifies supervised learning for beginners with a step-by-step interactive approach. Working with real-time datasets, you’ll learn how supervised learning, when used with Python, can produce efficient predictive models.Starting with the fundamentals of supervised learning, you’ll quickly move to understand how to automate manual tasks and the process of assessing date using Jupyter and Python libraries like pandas. Next, you’ll use data exploration and visualization techniques to develop powerful supervised learning models, before understanding how to distinguish variables and represent their relationships using scatter plots, heatmaps, and box plots. After using regression and classification models on real-time datasets to predict future outcomes, you’ll grasp advanced ensemble techniques such as boosting and random forests. Finally, you’ll learn the importance of model evaluation in supervised learning and study metrics to evaluate regression and classification tasks.By the end of this book, you’ll have the skills you need to work on your real-life supervised learning Python projects.
Matthew Moocarme, Abhranshu Bagchi, Anthony So ,...
Getting to grips with tensors, deep learning, and neural networks can be intimidating and confusing for anyone, no matter their experience level. The breadth of information out there, often written at a very high level and aimed at advanced practitioners, can make getting started even more challenging.If this sounds familiar to you, The TensorFlow Workshop is here to help. Combining clear explanations, realistic examples, and plenty of hands-on practice, it’ll quickly get you up and running.You’ll start off with the basics – learning how to load data into TensorFlow, perform tensor operations, and utilize common optimizers and activation functions. As you progress, you’ll experiment with different TensorFlow development tools, including TensorBoard, TensorFlow Hub, and Google Colab, before moving on to solve regression and classification problems with sequential models.Building on this solid foundation, you’ll learn how to tune models and work with different types of neural network, getting hands-on with real-world deep learning applications such as text encoding, temperature forecasting, image augmentation, and audio processing.By the end of this deep learning book, you’ll have the skills, knowledge, and confidence to tackle your own ambitious deep learning projects with TensorFlow.
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, Fourth 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 fourth 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 engineer, platform engineer, or software architect, this book equips you with the skills and understanding needed to build secure, scalable, and future-ready container platforms.
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.
Aaron Jones , Christopher Kruger , Benjamin...
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.
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.
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.
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.
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