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Podcasts
Argo CD in Practice. The GitOps way of managing cloud-native applications
Liviu Costea, Spiros Economakis, Alexander Matyushentsev
GitOps follows the practices of infrastructure as code (IaC), allowing developers to use their day-to-day tools and practices such as source control and pull requests to manage apps. With this book, you’ll understand how to apply GitOps bootstrap clusters in a repeatable manner, build CD pipelines for cloud-native apps running on Kubernetes, and minimize the failure of deployments.You’ll start by installing Argo CD in a cluster, setting up user access using single sign-on, performing declarative configuration changes, and enabling observability and disaster recovery. Once you have a production-ready setup of Argo CD, you’ll explore how CD pipelines can be built using the pull method, how that increases security, and how the reconciliation process occurs when multi-cluster scenarios are involved. Next, you’ll go through the common troubleshooting scenarios, from installation to day-to-day operations, and learn how performance can be improved. Later, you’ll explore the tools that can be used to parse the YAML you write for deploying apps. You can then check if it is valid for new versions of Kubernetes, verify if it has any security or compliance misconfigurations, and that it follows the best practices for cloud-native apps running on Kubernetes.By the end of this book, you’ll be able to build a real-world CD pipeline using Argo CD.
Want to model a 3D printed prototype of an object that needs to be replaced or broken? This book will teach you how to accurately measure objects in the real world with a few basic measuring techniques and how to create an object for 3D printing around the objects measured. In this book, you'll learn to identify basic shapes from a given object, use Vernier and Digital calipers and grid paper tracing techniques to derive measurements for the objects. With the help of measurements, you'll see to model these objects using Blender, organize the parts into layers, and later combine them to create the desired object, which in this book is a 3D printable SD card holder ring that fits your finger.
Shaun Bryant, Jessica Langston, Jeanne Aarhus
AutoCAD helps you communicate your design intent by plotting your designs to drawings, in both paper and electronic format. But using AutoCAD can be daunting, even for an experienced user who wants to get their designs into the AutoCAD native DWG file format.Written by an Autodesk Certified Instructor at Platinum level with 30+ years of industry experience, this book will guide you on how to use new and existing AutoCAD tools to work smarter, not harder, and it will familiarize you with the processes needed to use AutoCAD much more effectively. As you work through the chapters, you’ll get used to these new methodologies in AutoCAD and build up muscle memory so that these skills become second nature. You’ll also take advantage of the author's expertise and experience, learning some highly effective AutoCAD tips and tricks along the way.By the end of this AutoCAD book, you’ll have gained valuable insights into the knowledge needed to confidently prepare for your Autodesk AutoCAD certification.
David Millán Escrivá, Vinícius G. Mendonça, Prateek Joshi
OpenCV is one of the best open source libraries available, and can help you focus on constructing complete projects on image processing, motion detection, and image segmentation. Whether you’re completely new to computer vision, or have a basic understanding of its concepts, Learn OpenCV 4 by Building Projects – Second edition will be your guide to understanding OpenCV concepts and algorithms through real-world examples and projects. You’ll begin with the installation of OpenCV and the basics of image processing. Then, you’ll cover user interfaces and get deeper into image processing. As you progress through the book, you'll learn complex computer vision algorithms and explore machine learning and face detection. The book then guides you in creating optical flow video analysis and background subtraction in complex scenes. In the concluding chapters, you'll also learn about text segmentation and recognition and understand the basics of the new and improved deep learning module.By the end of this book, you'll be familiar with the basics of Open CV, such as matrix operations, filters, and histograms, and you'll have mastered commonly used computer vision techniques to build OpenCV projects from scratch.
Generative AI Foundations in Python. Discover key techniques and navigate modern challenges in LLMs
Carlos Rodriguez, Samira Shaikh
The intricacies and breadth of generative AI (GenAI) and large language models can sometimes eclipse their practical application. It is pivotal to understand the foundational concepts needed to implement generative AI. This guide explains the core concepts behind -of-the-art generative models by combining theory and hands-on application.Generative AI Foundations in Python begins by laying a foundational understanding, presenting the fundamentals of generative LLMs and their historical evolution, while also setting the stage for deeper exploration. You’ll also understand how to apply generative LLMs in real-world applications. The book cuts through the complexity and offers actionable guidance on deploying and fine-tuning pre-trained language models with Python. Later, you’ll delve into topics such as task-specific fine-tuning, domain adaptation, prompt engineering, quantitative evaluation, and responsible AI, focusing on how to effectively and responsibly use generative LLMs.By the end of this book, you’ll be well-versed in applying generative AI capabilities to real-world problems, confidently navigating its enormous potential ethically and responsibly.
Aaron Jones, Christopher Kruger, Benjamin Johnston
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.