Programowanie
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.
The Software Engineer's Library. A runbook for building reliable systems and a resilient career
Michelle Brenner
If you are daunted by the skills required to thrive as a Senior Software Engineer, this book will help you acquire them and crush any lingering impostor syndrome. It’s a practical, interactive guide to real-world technical leadership. Senior engineers are expected to grow their influence with larger projects, inspiring their team and influencing cross-functional stakeholders for better results. Inside, you’ll cover topics from designing distributed systems to collaborating with any peer, stakeholder, or manager. The book encourages skill-building through hands-on exercises, relatable case studies, and a dash of humor to keep things lively. It also shows how AI can make your work more effective and less stressful, without replacing your unique and hard-earned skills. What sets this book apart? You’ll craft a single app from idea to scale, solving both technical and people challenges. Along the way, you’ll learn from engineers worldwide, each sharing their approach to overcoming obstacles. Whether you’re working through the book yourself or helping a peer level up, you'll find strategies for communication, mentorship, and career development. Jump into any section you need to discover your next step, build your MVP, navigate growth, or focus on life outside work. We’ll learn, grow, and have some fun!
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
Time Series with PyTorch. Modern Deep Learning Toolkit for Real-World Forecasting Challenges
Graeme Davidson, Lei Ma
Neural networks are powerful tools for time-series forecasting, but applying them effectively requires both practical experience and a clear understanding of architectures, training strategies, and evaluation methods. This book brings these ideas together in a structured and practical way.Starting with PyTorch fundamentals, you will build neural networks from scratch and progress through recurrent networks, attention mechanisms, and transformers before exploring forecasting architectures such as N-BEATS, N-HiTS, and the Temporal Fusion Transformer. Along the way, you will learn robust hyperparameter tuning, conformal prediction for uncertainty estimation, and reliable evaluation practices.Unlike most forecasting books, this text also explores topics often overlooked or treated separately, including transfer learning across collections of series, synthetic data generation with diffusion models, and self-supervised representation learning. Beyond forecasting, later chapters cover classification, clustering, anomaly detection, and embeddings for large-scale time-series modeling.Throughout, the focus is pragmatic: theory is reinforced through experimentation and implementation so you can apply these methods confidently to real-world time-series problems.
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.
Alejandro Rodas de Paz
As one of the more versatile programming languages, Python is well-known for its batteries-included philosophy, which includes a rich set of modules in its standard library; Tkinter is the library included for building desktop applications. Due to this, Tkinter is a common choice for rapid GUI development, and more complex applications can benefit from the full capabilities of this library. This book covers all of your Tkinter and Python GUI development problems and solutions.Tkinter GUI Application Development Cookbook starts with an overview of Tkinter classes and at the same time provides recipes for basic topics, such as layout patterns and event handling. Next, we cover how to develop common GUI patterns, such as entering and saving data, navigating through menus and dialogs, and performing long-running actions in the background.You can then make your apps leverage network resources effectively and perform graphical operations on a canvas and related tasks such as detecting collisions between items. Finally, this book covers using themed widgets, an extension of Tk widgets that have a more native look and feel. Finally, this book covers using the canvas and themed widgets.By the end of the book, you will have an in-depth knowledge of Tkinter classes, and will know how to use them to build efficient and rich GUI applications.
David Love
Tkinter is a modular, cross-platform application development toolkit for Python. When developing GUI-rich applications, the most important choices are which programming language(s) and which GUI framework to use. Python and Tkinter prove to be a great combination. This book will get you familiar with Tkinter by having you create fun and interactive projects. These projects have varying degrees of complexity. We'll start with a simple project, where you'll learn the fundamentals of GUI programming and the basics of working with a Tkinter application. After getting the basics right, we'll move on to creating a project of slightly increased complexity, such as a highly customizable Python editor. In the next project, we'll crank up the complexity level to create an instant messaging app. Toward the end, we'll discuss various ways of packaging our applications so that they can be shared and installed on other machines without the user having to learn how to install and run Python programs.
Mark J. Price
.NET is more powerful—and more complex—than ever. As the ecosystem evolves, so do the expectations from developers. Mastering the tools and patterns of professional .NET development can be the difference between simply shipping code and delivering resilient, scalable software. Tools and Skills for .NET 10 is a practical guide to leveling up in today’s .NET world, offering both hard technical skills and career strategies to help you thrive.Inside, you’ll learn how to manage codebases with Git and implement debugging and memory analysis techniques that save hours of guesswork. The book also covers best practices for writing and maintaining documentation for your code, services, and APIs, which is crucial for team collaboration. You’ll explore cryptography for securing data and concurrency for building responsive apps. Further chapters explore dependency injection, testing for performance and reliability, and packaging your apps in Docker containers.By the end of this book, you’ll be equipped not only with technical skills but also with the confidence to apply them in real environments. Whether you're aiming for a promotion, switching jobs, or preparing for technical interviews, you'll have the skills and the language to present yourself as a capable, well-rounded .NET developer ready for anything the industry throws at you.
DAVID WYAND
Torque 3D is a popular game engine that supports you in every step along the way to making your game a reality. Even with all of the power and tools that Torque 3D provides, finishing a high quality 3D game requires time and knowledge.Torque 3D Game Development Cookbook is a practical guide that takes you through each of the major steps on the journey to creating your game, while learning a few tricks along the way.The recipes in this book start off with learning some of the finer points about TorqueScript. The book then moves on to each of Torque 3D's subsystems and ends with a variety of game play recipes.The various topics covered include activating level-specific game code and scheduling game events, dragging and dropping items between windows to work with an in-game inventory system, and covering the seams between objects with well placed decals. Some of the advanced topics include writing custom shaders and postFX, using zones to improve rendering performance, and enhancing your game's ambience through sound.Once you are done with Torque 3D Game Development Cookbook you'll be on your way to creating amazing 3D games and gain expert knowledge of Torque 3D.
Curtis Miller
Python's ease-of-use and multi-purpose nature has made it one of the most popular tools for data scientists and machine learning developers. Its rich libraries are widely used for data analysis, and more importantly, for building state-of-the-art predictive models. This book is designed to guide you through using these libraries to implement effective statistical models for predictive analytics.You’ll start by delving into classical statistical analysis, where you will learn to compute descriptive statistics using pandas. You will focus on supervised learning, which will help you explore the principles of machine learning and train different machine learning models from scratch. Next, you will work with binary prediction models, such as data classification using k-nearest neighbors, decision trees, and random forests. The book will also cover algorithms for regression analysis, such as ridge and lasso regression, and their implementation in Python. In later chapters, you will learn how neural networks can be trained and deployed for more accurate predictions, and understand which Python libraries can be used to implement them.By the end of this book, you will have the knowledge you need to design, build, and deploy enterprise-grade statistical models for machine learning using Python and its rich ecosystem of libraries for predictive analytics.
Denis Rothman
The transformer architecture has proved to be revolutionary in outperforming the classical RNN and CNN models in use today. With an apply-as-you-learn approach, Transformers for Natural Language Processing investigates in vast detail the deep learning for machine translations, speech-to-text, text-to-speech, language modeling, question answering, and many more NLP domains with transformers.The book takes you through NLP with Python and examines various eminent models and datasets within the transformer architecture created by pioneers such as Google, Facebook, Microsoft, OpenAI, and Hugging Face.The book trains you in three stages. The first stage introduces you to transformer architectures, starting with the original transformer, before moving on to RoBERTa, BERT, and DistilBERT models. You will discover training methods for smaller transformers that can outperform GPT-3 in some cases. In the second stage, you will apply transformers for Natural Language Understanding (NLU) and Natural Language Generation (NLG). Finally, the third stage will help you grasp advanced language understanding techniques such as optimizing social network datasets and fake news identification.By the end of this NLP book, you will understand transformers from a cognitive science perspective and be proficient in applying pretrained transformer models by tech giants to various datasets.
Jeroen Mulder, Henry Mulder
Healthcare today faces a multitude of challenges, which can be summed up as the barriers architects and consultants face in transforming the healthcare system into a more sustainable one. This book helps you to guide that transformation step by step.You’ll begin by understanding the need for this transformation, exploring related challenges, the possibilities of technology, and how human factors can be involved in digital transformation. The book will enable you to overcome inhibitions and plan various transformation steps using the Transformation into Sustainable Healthcare (TiSH) model and DevOps4Care. Next, you’ll use the observe, orient, decide, and act (OODA) loop as an iterative approach to address all stakeholders and adapt swiftly when situations change. Further, you’ll be able to build shared platforms that enable interaction between various stakeholders, including the technology-enabled care service teams. The final chapters will help you execute the transformation to sustainable healthcare using the knowledge you’ve gained while getting familiar with common pitfalls and learning how to avoid or mitigate them.By the end of this DevOps book, you will have an overview of the challenges, opportunities, and directions of solutions and be on your way toward starting the transformation into sustainable healthcare.
Ken Fogel
This comprehensive guide will help non-Java developers already using different languages transition from their current language to all things Java. The chapters are designed in a way that re-enforces a developer’s existing knowledge of object-oriented methodologies as they apply to Java.This book has been divided into four sections, with each section touching upon different aspects that’ll enable your effective transition. The first section helps you get to grips with the Java development environment and the Maven build tool for modern Java applications. In the second section, you’ll learn about Java language fundamentals, along with exploring object-oriented programming (OOP) methodologies and functional programming and discovering how to implement software design patterns in Java. The third section shows you how to code in Java on different platforms and helps you get familiar with the challenges faced on these platforms. In the fourth section, you’ll find out how you can manage and package your Java code.By the end of this Java programming book, you’ll have learned the core concepts of Java that’ll help you successfully transition from a different language to Java.