Cisco ACI: Zero to HeroIt doesn't matter if you are completely new to Cisco ACI or you already have some experience with the technology, this book will guide you through the whole implementation lifecycle and provide you with a comprehensive toolset to become confident in any ACI-related task.
In the beginning, it's very important to build strong fundamental knowledge about Cisco ACI components. We'll go through underlay networking based on Nexus 9000 switches and describe the APIC controller cluster acting as the management plane of ACI. By building Access Policies, you'll see how to optimally connect servers, storage, routers, switches, or L4-L7 service devices to ACI. Then we'll properly design and implement Logical Application Policies. You will understand all the fabric forwarding behavior when using different ACI settings and architectures while getting a toolset on how to verify and troubleshoot eventual problems.
This book also covers external L2 and L3 connectivity in ACI, more advanced feat ...
Advanced Data Analytics Using Python, 2nd EditionUnderstand advanced data analytics concepts such as time series and principal component analysis with ETL, supervised learning, and PySpark using Python. This book covers architectural patterns in data analytics, text and image classification, optimization techniques, natural language processing, and computer vision in the cloud environment.
Generic design patterns in Python programming is clearly explained, emphasizing architectural practices such as hot potato anti-patterns. You'll review recent advances in databases such as Neo4j, Elasticsearch, and MongoDB. You'll then study feature engineering in images and texts with implementing business logic and see how to build machine learning and deep learning models using transfer learning.
Advanced Analytics with Python, 2nd edition features a chapter on clustering with a neural network, regularization techniques, and algorithmic design patterns in data analytics with reinforcement learning. Finally, the recommender system in PySpa ...
A Practical Guide to Cloud MigrationWhy do enterprises feel daunted when undertaking a large-scale cloud transformation? A move to the cloud usually offers substantial rewards. Once companies make this transition, they unlock new business opportunities that fundamentally change the way they work. With this report, members of the Google team will show you how to navigate the cultural and technological transformation required to migrate to the cloud.
Although Google is a company born in the cloud, several team members came from organizations that had to painstakingly work through this transition. They share their hard-won experience as they guide you through 13 essays covering the different aspects of a successful cloud transformation, including:
- Managing a Successful Transformation
- Celebrating (and Tweaking) Your Culture
- Framing Your Transformation with Clearly Articulated Policies
- Building Leadership Through Decider Groups
- Developing Centers of Excellence
- Scaling Innovation ...
Kubernetes Patterns, 2nd EditionThe way developers design, build, and run software has changed significantly with the evolution of microservices and containers. These modern architectures offer new distributed primitives that require a different set of practices than many developers, tech leads, and architects are accustomed to. With this focused guide, Bilgin Ibryam and Roland Huss provide common reusable patterns and principles for designing and implementing cloud native applications on Kubernetes.
Each pattern includes a description of the problem and a Kubernetes-specific solution. All patterns are backed by and demonstrated with concrete code examples. This updated edition is ideal for developers and architects familiar with basic Kubernetes concepts who want to learn how to solve common cloud native challenges with proven design patterns.
You'll explore: Foundational patterns covering core principles and practices for building and running container-based cloud native applications; Behavioral patterns that ...
Generative Deep Learning, 2nd EditionGenerative AI is the hottest topic in tech. This practical book teaches machine learning engineers and data scientists how to use TensorFlow and Keras to create impressive generative deep learning models from scratch, including variational autoencoders (VAEs), generative adversarial networks (GANs), Transformers, normalizing flows, energy-based models, and denoising diffusion models.
The book starts with the basics of deep learning and progresses to cutting-edge architectures. Through tips and tricks, you'll understand how to make your models learn more efficiently and become more creative.
Discover how VAEs can change facial expressions in photos; Train GANs to generate images based on your own dataset; Build diffusion models to produce new varieties of flowers; Train your own GPT for text generation; Learn how large language models like ChatGPT are trained; Explore state-of-the-art architectures such as StyleGAN2 and ViT-VQGAN; Compose polyphonic music using Transformers and Mu ...
Machine Learning for High-Risk ApplicationsThe past decade has witnessed the broad adoption of artificial intelligence and machine learning (AI/ML) technologies. However, a lack of oversight in their widespread implementation has resulted in some incidents and harmful outcomes that could have been avoided with proper risk management. Before we can realize AI/ML's true benefit, practitioners must understand how to mitigate its risks.
This book describes approaches to responsible AI - a holistic framework for improving AI/ML technology, business processes, and cultural competencies that builds on best practices in risk management, cybersecurity, data privacy, and applied social science. Authors Patrick Hall, James Curtis, and Parul Pandey created this guide for data scientists who want to improve real-world AI/ML system outcomes for organizations, consumers, and the public.
Learn technical approaches for responsible AI across explainability, model validation and debugging, bias management, data privacy, and ML security; Lea ...
Practical Data PrivacyBetween major privacy regulations like the GDPR and CCPA and expensive and notorious data breaches, there has never been so much pressure to ensure data privacy. Unfortunately, integrating privacy into data systems is still complicated. This essential guide will give you a fundamental understanding of modern privacy building blocks, like differential privacy, federated learning, and encrypted computation. Based on hard-won lessons, this book provides solid advice and best practices for integrating breakthrough privacy-enhancing technologies into production systems.
Practical Data Privacy answers important questions such as: What do privacy regulations like GDPR and CCPA mean for my data workflows and data science use cases? What does "anonymized data" really mean? How do I actually anonymize data? How does federated learning and analysis work? Homomorphic encryption sounds great, but is it ready for use? How do I compare and choose the best privacy-preserving technologies and method ...
Practical Linux System AdministrationThis essential guide covers all aspects of Linux system administration, from user maintenance, backups, filesystem housekeeping, storage management, and network setup to hardware and software troubleshooting and some application management. It's both a practical daily reference manual for sysadmins and IT pros and a handy study guide for those taking Linux certification exams.
You'll turn to it frequently, not only because of the sheer volume of valuable information it provides but because of the real-world examples within and the clear, useful way the information is presented. With this book at your side, you'll be able to: Install Linux and perform initial setup duties, such as connecting to a network; Navigate the Linux filesystem via the command line; Install software from repositories and source and satisfy dependencies; Set permissions on files and directories; Create, modify, and remove user accounts; Set up networking; Format and mount filesystems; Perform basic troubleshoot ...
Resilient Oracle PL/SQLAs legacy and other critical systems continue to migrate online, the need for continuous operation is imperative. Code has to handle data issues as well as hard external problems today, including outages of networks, storage systems, power, and ancillary systems. This practical guide provides system administrators, DevSecOps engineers, and cloud architects with a concise yet comprehensive overview on how to use PL/SQL to develop resilient database solutions.
Integration specialist Stephen B Morris helps you understand the language, build a PL/SQL toolkit, and collect a suite of reusable components and patterns. You'll dive into the benefits of synthesizing the toolkit with a requirements-driven, feature-oriented approach and learn how to produce resilient solutions by synthesizing the PL/SQL toolkit in conjunction with a scale of resilience.
Build solid PL/SQL solutions while avoiding common PL/SQL antipatterns; Learn why embedding complex business logic in SQL is often a brittle ...
Machine Learning for Cyber Physical SystemsThis open proceedings presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains selected papers from the fifth international Conference ML4CPS - Machine Learning for Cyber Physical Systems, which was held in Berlin, March 12-13, 2020. Cyber Physical Systems are characterized by their ability to adapt and to learn: They analyze their environment and, based on observations, they learn patterns, correlations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnosis. Machine Learning is the key technology for these developments.The EditorsProf. Dr.-Ing. Jurgen Beyerer is Professor at the Department for Interactive Real-Time Systems at the Karlsruhe Institute of Technology. In addition he manages the Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB.Dr. Alexander Maier is head of group Machine Learning at Fraunhofer IOSB-INA. His focus is on ...