Explainable AI for Practitioners
Most intermediate-level machine learning books focus on how to optimize models by increasing accuracy or decreasing prediction error. But this approach often overlooks the importance of understanding why and how your ML model makes the predictions that it does. Explainability methods provide an essential toolkit for better understanding model behavior, and this practical guide brings together best-in-class techniques for model explainability. Experienced machine learning engineers and data scientists will learn hands-on how these techniques work so that you'll be able to apply these tools more easily in your daily workflow. ...
Most intermediate-level machine learning books focus on how to optimize models by increasing accuracy or decreasing prediction error. But this approach often overlooks the importance of understanding why and how your ML model makes the predictions that it does. Explainability methods provide an essential toolkit for better understanding model behavior, and this practical guide brings together best-in-class techniques for model explainability. Experienced machine learning engineers and data scientists will learn hands-on how these techniques work so that you'll be able to apply these tools more easily in your daily workflow. ...
Version Control with Git, 3rd Edition
Track, branch, merge, and manage code revisions with Git, the free and open source distributed version control system. Through a series of step-by-step tutorials, this practical guide quickly takes you from Git fundamentals to advanced techniques, and provides friendly yet rigorous advice for navigating Git's many functions. You'll learn how to work with everything from small to very large projects with speed and efficiency. In this third edition, authors Prem Kumar Ponuthorai and Jon Loeliger break down Git concepts using a modular approach. You'll start with the basics and fundamental philosophy of Git, followed by intermediate commands to help you efficiently supplement your daily development workflow. Finally, you'll learn advanced Git commands and concepts to understand how Git works under the hood. ...
Track, branch, merge, and manage code revisions with Git, the free and open source distributed version control system. Through a series of step-by-step tutorials, this practical guide quickly takes you from Git fundamentals to advanced techniques, and provides friendly yet rigorous advice for navigating Git's many functions. You'll learn how to work with everything from small to very large projects with speed and efficiency. In this third edition, authors Prem Kumar Ponuthorai and Jon Loeliger break down Git concepts using a modular approach. You'll start with the basics and fundamental philosophy of Git, followed by intermediate commands to help you efficiently supplement your daily development workflow. Finally, you'll learn advanced Git commands and concepts to understand how Git works under the hood. ...
Python Feature Engineering Cookbook, 2nd Edition
Feature engineering, the process of transforming variables and creating features, albeit time-consuming, ensures that your machine learning models perform seamlessly. This second edition of Python Feature Engineering Cookbook will take the struggle out of feature engineering by showing you how to use open source Python libraries to accelerate the process via a plethora of practical, hands-on recipes. This updated edition begins by addressing fundamental data challenges such as missing data and categorical values, before moving on to strategies for dealing with skewed distributions and outliers. The concluding chapters show you how to develop new features from various types of data, including text, time series, and relational databases. With the help of numerous open source Python libraries, you'll learn how to implement each feature engineering method in a performant, reproducible, and elegant manner. By the end of this Python book, you will have the tools and expertise needed to ...
Feature engineering, the process of transforming variables and creating features, albeit time-consuming, ensures that your machine learning models perform seamlessly. This second edition of Python Feature Engineering Cookbook will take the struggle out of feature engineering by showing you how to use open source Python libraries to accelerate the process via a plethora of practical, hands-on recipes. This updated edition begins by addressing fundamental data challenges such as missing data and categorical values, before moving on to strategies for dealing with skewed distributions and outliers. The concluding chapters show you how to develop new features from various types of data, including text, time series, and relational databases. With the help of numerous open source Python libraries, you'll learn how to implement each feature engineering method in a performant, reproducible, and elegant manner. By the end of this Python book, you will have the tools and expertise needed to ...
Ansible for Real-Life Automation
Get ready to leverage the power of Ansible's wide applicability to automate and manage IT infrastructure with Ansible for Real-Life Automation. This book will guide you in setting up and managing the free and open source automation tool and remote-managed nodes in the production and dev/staging environments. Starting with its installation and deployment, you'll learn automation using simple use cases in your workplace. You'll go beyond just Linux machines to use Ansible to automate Microsoft Windows machines, network devices, and private and public cloud platforms such as VMWare, AWS, and GCP. As you progress through the chapters, you'll integrate Ansible into your DevOps workflow and deal with application container management and container platforms such as Kubernetes. This Ansible book also contains a detailed introduction to Red Hat Ansible Automation Platform to help you get up to speed with Red Hat AAP and integration with CI/CD and ITSM. What's more, you'll implement effici ...
Get ready to leverage the power of Ansible's wide applicability to automate and manage IT infrastructure with Ansible for Real-Life Automation. This book will guide you in setting up and managing the free and open source automation tool and remote-managed nodes in the production and dev/staging environments. Starting with its installation and deployment, you'll learn automation using simple use cases in your workplace. You'll go beyond just Linux machines to use Ansible to automate Microsoft Windows machines, network devices, and private and public cloud platforms such as VMWare, AWS, and GCP. As you progress through the chapters, you'll integrate Ansible into your DevOps workflow and deal with application container management and container platforms such as Kubernetes. This Ansible book also contains a detailed introduction to Red Hat Ansible Automation Platform to help you get up to speed with Red Hat AAP and integration with CI/CD and ITSM. What's more, you'll implement effici ...
Deep Learning for Natural Language Processing
Deep learning has advanced natural language processing to exciting new levels and powerful new applications! For the first time, computer systems can achieve "human" levels of summarizing, making connections, and other tasks that require comprehension and context. Deep Learning for Natural Language Processing reveals the groundbreaking techniques that make these innovations possible. Stephan Raaijmakers distills his extensive knowledge into useful best practices, real-world applications, and the inner workings of top NLP algorithms. Deep learning has transformed the field of natural language processing. Neural networks recognize not just words and phrases, but also patterns. Models infer meaning from context, and determine emotional tone. Powerful deep learning-based NLP models open up a goldmine of potential uses. Deep Learning for Natural Language Processing teaches you how to create advanced NLP applications using Python and the Keras deep learning library. You'll learn to use ...
Deep learning has advanced natural language processing to exciting new levels and powerful new applications! For the first time, computer systems can achieve "human" levels of summarizing, making connections, and other tasks that require comprehension and context. Deep Learning for Natural Language Processing reveals the groundbreaking techniques that make these innovations possible. Stephan Raaijmakers distills his extensive knowledge into useful best practices, real-world applications, and the inner workings of top NLP algorithms. Deep learning has transformed the field of natural language processing. Neural networks recognize not just words and phrases, but also patterns. Models infer meaning from context, and determine emotional tone. Powerful deep learning-based NLP models open up a goldmine of potential uses. Deep Learning for Natural Language Processing teaches you how to create advanced NLP applications using Python and the Keras deep learning library. You'll learn to use ...
AWS for Non-Engineers
AWS for Non-engineers is for anyone just starting with Amazon Web Services or cloud computing in general - whether you're in customer service, marketing, or management. It's written by Hiroko Nishimura, and is based on her acclaimed video courses that have been taken by over 300,000 learners. In this reader-friendly book, you'll learn how to talk about cloud concepts with engineers, what the cloud could do for your business, and how to start using AWS's amazing services for your own IT tasks. When you're finished, you'll be comfortable with the basics of cloud computing on AWS and you'll be prepared to take the AWS Certified Cloud Practitioner Exam! Millions of companies use Amazon Web Services (AWS) to share documents, run business applications, and store important data. Learning the basics of AWS is a required skill, and this book makes it easy! There's no geeky jargon nor complex code - just crystal-clear explanations of the AWS features you'll use every day. You'll even get tips ...
AWS for Non-engineers is for anyone just starting with Amazon Web Services or cloud computing in general - whether you're in customer service, marketing, or management. It's written by Hiroko Nishimura, and is based on her acclaimed video courses that have been taken by over 300,000 learners. In this reader-friendly book, you'll learn how to talk about cloud concepts with engineers, what the cloud could do for your business, and how to start using AWS's amazing services for your own IT tasks. When you're finished, you'll be comfortable with the basics of cloud computing on AWS and you'll be prepared to take the AWS Certified Cloud Practitioner Exam! Millions of companies use Amazon Web Services (AWS) to share documents, run business applications, and store important data. Learning the basics of AWS is a required skill, and this book makes it easy! There's no geeky jargon nor complex code - just crystal-clear explanations of the AWS features you'll use every day. You'll even get tips ...
Create Graphical User Interfaces with Python
Add buttons, boxes, pictures and colours and more to your Python programs using the guizero library, which is quick, accessible, and understandable for all. This 156-page book is suitable for everyone, from beginners to experienced Python programmers who want to explore graphical user interfaces (GUIs). There are ten fun projects for you to create, including a painting program, an emoji match game, and a stop-motion animation creator. - Create games and fun Python programs; - Learn how to create your own graphical user interfaces; - Use windows, text boxes, buttons, images, and more; - Learn about event-based programming; - Explore good (and bad) user interface design. ...
Add buttons, boxes, pictures and colours and more to your Python programs using the guizero library, which is quick, accessible, and understandable for all. This 156-page book is suitable for everyone, from beginners to experienced Python programmers who want to explore graphical user interfaces (GUIs). There are ten fun projects for you to create, including a painting program, an emoji match game, and a stop-motion animation creator. - Create games and fun Python programs; - Learn how to create your own graphical user interfaces; - Use windows, text boxes, buttons, images, and more; - Learn about event-based programming; - Explore good (and bad) user interface design. ...
Mathematics for Game Programming and Computer Graphics
Mathematics is an essential skill when it comes to graphics and game development, particularly if you want to understand the generation of real-time computer graphics and the manipulation of objects and environments in a detailed way. Python, together with Pygame and PyOpenGL, provides you with the opportunity to explore these features under the hood, revealing how computers generate and manipulate 3D environments. Mathematics for Game Programming and Computer Graphics is an exhaustive guide to getting "back to the basics" of mathematics, using a series of problem-based, practical exercises to explore ideas around drawing graphic lines and shapes, applying vectors and vertices, constructing and rendering meshes, and working with vertex shaders. By leveraging Python, Pygame, and PyOpenGL, you'll be able to create your own mathematics-based engine and API that will be used throughout to build applications. By the end of this graphics focussed book, you'll have gained a thorough und ...
Mathematics is an essential skill when it comes to graphics and game development, particularly if you want to understand the generation of real-time computer graphics and the manipulation of objects and environments in a detailed way. Python, together with Pygame and PyOpenGL, provides you with the opportunity to explore these features under the hood, revealing how computers generate and manipulate 3D environments. Mathematics for Game Programming and Computer Graphics is an exhaustive guide to getting "back to the basics" of mathematics, using a series of problem-based, practical exercises to explore ideas around drawing graphic lines and shapes, applying vectors and vertices, constructing and rendering meshes, and working with vertex shaders. By leveraging Python, Pygame, and PyOpenGL, you'll be able to create your own mathematics-based engine and API that will be used throughout to build applications. By the end of this graphics focussed book, you'll have gained a thorough und ...
Applying Math with Python, 2nd Edition
The updated edition of Applying Math with Python will help you solve complex problems in a wide variety of mathematical fields in simple and efficient ways. Old recipes have been revised for new libraries and several recipes have been added to demonstrate new tools such as JAX. You'll start by refreshing your knowledge of several core mathematical fields and learn about packages covered in Python's scientific stack, including NumPy, SciPy, and Matplotlib. As you progress, you'll gradually get to grips with more advanced topics of calculus, probability, and networks (graph theory). Once you've developed a solid base in these topics, you'll have the confidence to set out on math adventures with Python as you explore Python's applications in data science and statistics, forecasting, geometry, and optimization. The final chapters will take you through a collection of miscellaneous problems, including working with specific data formats and accelerating code. By the end of this book, y ...
The updated edition of Applying Math with Python will help you solve complex problems in a wide variety of mathematical fields in simple and efficient ways. Old recipes have been revised for new libraries and several recipes have been added to demonstrate new tools such as JAX. You'll start by refreshing your knowledge of several core mathematical fields and learn about packages covered in Python's scientific stack, including NumPy, SciPy, and Matplotlib. As you progress, you'll gradually get to grips with more advanced topics of calculus, probability, and networks (graph theory). Once you've developed a solid base in these topics, you'll have the confidence to set out on math adventures with Python as you explore Python's applications in data science and statistics, forecasting, geometry, and optimization. The final chapters will take you through a collection of miscellaneous problems, including working with specific data formats and accelerating code. By the end of this book, y ...
Designing Event-Driven Systems
Many forces affect software today: larger datasets, geographical disparities, complex company structures, and the growing need to be fast and nimble in the face of change. Proven approaches such as service-oriented and event-driven architectures are joined by newer techniques such as microservices, reactive architectures, DevOps, and stream processing. Many of these patterns are successful by themselves, but as this practical ebook demonstrates, they provide a more holistic and compelling approach when applied together. Author Ben Stopford explains how service-based architectures and stream processing tools such as Apache Kafka can help you build business-critical systems. You'll learn how to apply patterns including Event Sourcing and CQRS, and how to build multi-team systems with microservices and SOA using patterns such as "inside out databases" and "event streams as a source of truth." These approaches provide a unique foundation for how these large, autonomous service ecosystem ...
Many forces affect software today: larger datasets, geographical disparities, complex company structures, and the growing need to be fast and nimble in the face of change. Proven approaches such as service-oriented and event-driven architectures are joined by newer techniques such as microservices, reactive architectures, DevOps, and stream processing. Many of these patterns are successful by themselves, but as this practical ebook demonstrates, they provide a more holistic and compelling approach when applied together. Author Ben Stopford explains how service-based architectures and stream processing tools such as Apache Kafka can help you build business-critical systems. You'll learn how to apply patterns including Event Sourcing and CQRS, and how to build multi-team systems with microservices and SOA using patterns such as "inside out databases" and "event streams as a source of truth." These approaches provide a unique foundation for how these large, autonomous service ecosystem ...