Practical techniques for writing code that is robust, reliable, and easy for team members to understand and adapt. In Good Code, Bad Code you’ll learn how to: Think about code like an effective software engineer, write functions that read like well-structured sentences, ensure code is reliable and bug free, effectively unit test code, identify code that can cause problems and improve it, write code that is reusable and adaptable to new requirements, improve your medium and long-term productivity, and save yourself and your team time.

Dave Thomas and Andy Hunt wrote the first edition of this influential book in 1999 to help their clients create better software and rediscover the joy of coding. These lessons have helped a generation of programmers examine the very essence of software development. Now, 20 years later, this new edition re-examines what it means to be a modern programmer. Topics range from personal responsibility and career development to architectural techniques for keeping your code flexible and easy to adapt and reuse.

In Modern Software Engineering, continuous delivery pioneer David Farley helps software professionals think about their work more effectively, manage it more successfully, and genuinely improve the quality of their applications, their lives, and the lives of their colleagues.

As a software engineer, you’ll encounter countless programming challenges that initially seem confusing, difficult, or even impossible. Don’t despair! Many of these “new” problems already have well-established solutions. Advanced Algorithms and Data Structures teaches you powerful approaches to a wide range of tricky coding challenges that you can adapt and apply to your own applications. Providing a balanced blend of classic, advanced, and new algorithms, this practical guide upgrades your programming toolbox with new perspectives and hands-on techniques.

Great software is something to marvel at: powerful, elegant, functional, a pleasure to work with as both a developer and as a user. Great software isn’t written by machines. It is written by professionals with an unshakable commitment to craftsmanship. The Clean Coder will help you become one of them - and earn the pride and fulfillment that they alone possess.

This book provides the first comprehensive overview of software architecture’s many aspects. Aspiring and existing architects alike will examine architectural characteristics, architectural patterns, component determination, diagramming and presenting architecture, evolutionary architecture, and many other topics. Mark Richards and Neal Ford—hands-on practitioners who have taught software architecture classes professionally for years—focus on architecture principles that apply across all technology stacks.

How can software engineers manage a living codebase that evolves and responds to changing requirements and demands over the length of its life? Based on their experience at Google, software engineers Titus Winters and Hyrum Wright, along with technical writer Tom Manshreck, present a candid and insightful look at how some of the world’s leading practitioners construct and maintain software. This book covers Google’s unique engineering culture, processes, and tools and how these aspects contribute to the effectiveness of an engineering organization.

Improving existing code - refactoring - is one of the most common tasks you’ll face as a programmer. Five Lines of Code teaches you clear and actionable refactoring rules that you can apply without relying on intuitive judgements such as “code smells”. Following the author’s expert perspective - that refactoring and code smells can be learned by following a concrete set of principles - you’ll learn when to refactor your code, what patterns to apply to what problem, and the code characteristics that indicate it’s time for a rework.

At most technology companies, you'll reach Senior software engineer, the career level for software engineers, in five to eight years. At the career level, your company's career ladder won't require that you work towards the next promotion; being promoted further is an exception rather than expected. This is also when many engineers are first given an opportunity to move into engineering management.

This friendly guide teaches you how to apply common algorithms to the practical problems you face every day as a programmer. You'll start with sorting and searching and, as you build up your skills in thinking algorithmically, you'll tackle more complex concerns such as data compression and artificial intelligence. This accesible introduction is suitable for self-taught programmers, engineers, or anyone who wants to brush up on algorithms. Each carefully presented example includes helpful diagrams and fully annotated code samples in Python.

Clean Architecture is an essential book for every current or aspiring software architect, systems analyst, system designer, and software manager - and for every programmer who must execute someone else’s designs.

Microservices Patterns teaches you how to develop and deploy production-quality microservices-based applications. This invaluable set of design patterns builds on decades of distributed system experience, adding new patterns for writing services and composing them into systems that scale and perform reliably under real-world conditions. More than just a patterns catalog, this practical guide offers experience-driven advice to help you design, implement, test, and deploy your microservices-based application.

Doom Guy: Life in First Person is the long-awaited autobiography of gaming’s original rock star and the cocreator of DOOM, Quake, and Wolfenstein—some of the most recognizable and important titles in video game history. Credited with the invention of the first-person shooter, a genre that continues to dominate the market today, he is gaming royalty. Told in remarkable detail, a byproduct of his hyperthymesia, Romero recounts his storied career.

Do you want to impress the processes that you are working on? Do you want to make your machines more intelligent? If your answer to any of those questions is yes, then you have come to the right place.This audiobook is a sequel to the book titled Machine Learning: A Step-by-Step Guide. In the first book, you gathered information on what machine learning is, and the different algorithms that one needs to know. This book is for those who have a basic understanding of what machine learning is.

Containers are revolutionizing the way we build, ship, and run our applications. But like all good things, they come with their own set of challenges. This is where Kubernetes enters the scene. Kubernetes helps you deploy and manage containerized applications at scale. With Kubernetes, you can develop your applications on your laptop, deploy to your chosen cloud platform, migrate to a different cloud platform, and even migrate to your private cloud at your on-premises datacenter.

Practical techniques for writing code that is robust, reliable, and easy for team members to understand and adapt. In Good Code, Bad Code you’ll learn how to: Think about code like an effective software engineer, write functions that read like well-structured sentences, ensure code is reliable and bug free, effectively unit test code, identify code that can cause problems and improve it, write code that is reusable and adaptable to new requirements, improve your medium and long-term productivity, and save yourself and your team time.

Natural Language Processing in Action is your guide to building machines that can read and interpret human language. In it, you'll use readily available Python packages to capture the meaning in text and react accordingly. The book expands traditional NLP approaches to include neural networks, modern deep learning algorithms, and generative techniques as you tackle real-world problems like extracting dates and names, composing text, and answering free-form questions.

Deep Learning with Python (Second Edition) introduces the field of deep learning using Python and the powerful Keras library. In this revised and expanded new edition, Keras creator François Chollet offers insights for both novice and experienced machine learning practitioners. As you move through this book, you’ll build your understanding through intuitive explanations and clear examples. You’ll quickly pick up the skills you need to start developing deep learning applications.

If you're looking to make a career move from programmer to AI specialist, this is the ideal place to start. Based on Laurence Moroney's extremely successful AI courses, this introductory book provides a hands-on, code-first approach to help you build confidence while you learn key topics.

Classic Computer Science Problems in Python sharpens your CS problem-solving skills with time-tested scenarios, exercises, and algorithms, using Python. You'll tackle dozens of coding challenges, ranging from simple tasks like binary search algorithms to clustering data using k-means. You'll especially enjoy the feeling of satisfaction as you crack problems that connect computer science to the real-world concerns of apps, data, performance, and even nailing your next job interview!