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.