Kubernetes radically changes the way applications are built and deployed in the cloud. Since its introduction in 2014, this container orchestrator has become one of the largest and most popular open source projects in the world. The updated edition of this practical book shows developers and ops personnel how Kubernetes and container technology can help you achieve new levels of velocity, agility, reliability, and efficiency.Kelsey Hightower, Brendan Burns, and Joe Bedawhove worked on Kubernetes at Google and beyondexplain how this system fits into the lifecycle of a distributed application.
Minimum quantity for "Kubernetes: Up and Running, Second Edition: Dive into the Future of Infrastructure" is 1.
Deep learning is changing everything. This machine-learning method has already surpassed traditional computer vision techniques, and the same is happening with NLP. If you're looking to bring deep learning into your domain, this practical book will bring you up to speed on key concepts using Facebook's PyTorch framework.Once author Ian Pointer helps you set up PyTorch on a cloud-based environment, you'll learn how use the framework to create neural architectures for performing operations on images, sound, text, and other types of data. By the end of the book, you'll be able to create neural networks and train them on multiple types of data.
Minimum quantity for "Programming PyTorch for Deep Learning: Creating and Deploying Deep Learning Applications" is 1.
Serverless computing greatly simplifies software development. Your team can focus solely on your application while the cloud provider manages the servers you need. This practical guide shows you step-by-step how to build and deploy complex applications in a flexible multicloud, multilanguage environment using Apache OpenWhisk. You’ll learn how this platform enables you to pursue a vendor-independent approach using preconfigured containers, microservices, and Kubernetes as your cloud operating system.
Minimum quantity for "Learning Apache OpenWhisk: Developing Open Serverless Solutions" is 1.
All Indian Reprints of O'Reilly are printed in Grayscale
Build your expertise in the BPF virtual machine in the Linux kernel with this practical guide for systems engineers. You'll not only dive into the BPF program lifecycle but also learn to write applications that observe and modify the kernel's behavior; inject code to monitor, trace, and securely observe events in the kernel; and more.Authors David Calavera and Lorenzo Fontana help you harness the power of BPF to make any computing system more observable. Familiarize yourself with the essential concepts you'll use on a day-to-day basis and augment your knowledge about performance optimization, networking, and security.
Minimum quantity for "Linux Observability with BPF: Advanced Programming for Performance Analysis and Networking" is 1.
Deep learning has already achieved remarkable results in many fields. Now its making waves throughout the sciences broadly and the life sciences in particular. This practical book teaches developers and scientists how to use deep learning for genomics, chemistry, biophysics, microscopy, medical analysis, and other fields.
Ideal for practicing developers and scientists ready to apply their skills to scientific applications such as biology, genetics, and drug discovery, this book introduces several deep network primitives. Youll follow a case study on the problem of designing new therapeutics that ties together physics, chemistry, biology, and medicinean example that represents one of sciences greatest challenges.
Learn the basics of performing machine learning on molecular data
Understand why deep learning is a powerful tool for genetics and genomics
Apply deep learning to understand biophysical systems
Get a brief introduction to machine learning with DeepChem
Use deep learning to analyze microscopic images
Analyze medical scans using deep learning techniques
Learn about variational autoencoders and generative adversarial networks
Interpret what your model is doing and how its working
Develop smart applications without spending days and weeks building machine-learning models. With this practical book, youll learn how to apply Automated Machine Learning, a process that uses machine learning to help people build machine learning models. Deepak Mukunthu, Parashar Shah, and Wee Hyong Tok provide a mix of technical depth, hands-on examples, and case studies that show how customers are solving real-world problems with this technology.Building machine learning models is an iterative and time-consuming process. Even those who know how to create these models may be limited in how much they can explore. Once you complete this book, youll understand how to apply Automated Machine Learning to your data right away.
Minimum quantity for "Practical Automated Machine Learning on Azure: Using Azure Machine Learning to Quickly Build AI Solutions" is 1.
Before you can build analytics tools to gain quick insights, you first need to know how to process data in real time. With this practical guide, developers familiar with Apache Spark will learn how to put this in-memory framework to use for streaming data. Youll discover how Spark enables you to write streaming jobs in almost the same way you write batch jobs.
Minimum quantity for "Stream Processing with Apache Spark: Mastering Structured Streaming and Spark Streaming" is 1.
A hands-on introduction to Packer, the HashiCorp image builder. Packer helps engineers, developers, sysadmins, and operations staff build multi-platform images including support for Docker containers, virtual machines, and Cloud-based images for platforms like Amazon Web Services and Google Cloud. Packer allows you to build consistent images on Linux, Microsoft Windows, macOS and other operating systems. In the book, we'll teach you how to install, use and integrate Packer into your environment and work flow.
Minimum quantity for "The Packer Book" is 1.
With the resurgence of neural networks in the 2010s, deep learning has become essential for machine learning practitioners and even many software engineers. This book provides a comprehensive introduction for data scientists and software engineers with machine learning experience. Youll start with deep learning basics and move quickly to the details of important advanced architectures, implementing everything from scratch along the way.Author Seth Weidman shows you how neural networks work using a first principles approach.
Minimum quantity for "Deep Learning From Scratch: Building with Python from First Principles" is 1.
Minimum quantity for "Cloud Native Transformation: Practical Patterns for Innovation" is 1.
Learn how graph algorithms can help you leverage relationships within your data to develop intelligent solutions and enhance your machine learning models. With this practical guide, developers and data scientists will discover how graph analytics deliver value, whether theyre used for building dynamic network models or forecasting real-world behavior.Mark Needham and Amy Hodler from Neo4j explain how graph algorithms describe complex structures and reveal difficult-to-find patternsfrom finding vulnerabilities and bottlenecks to detecting communities and improving machine learning predictions. Youll walk through hands-on examples that show you how to use graph algorithms in Apache Spark and Neo4j, two of the most common choices for graph analytics.
Minimum quantity for "Graph Algorithms: Practical Examples in Apache Spark and Neo4j" is 1.
The way developers design, build, and run software has changed significantly with the evolution of microservices and containers. These modern architectures use new primitives that require a different set of practices than most developers, tech leads, and architects are accustomed to. With this focused guide, Bilgin Ibryam and Roland Huß from Red Hat provide common reusable elements, patterns, principles, and practices for designing and implementing cloud-native applications on Kubernetes.
Minimum quantity for "Kubernetes Patterns: Reusable Elements for Designing Cloud-Native Applications" is 1.