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An understanding of psychologyspecifically the psychology behind how users behave and interact with digital interfacesis perhaps the single most valuable nondesign skill a designer can have. The most elegant design can fail if it forces users to conform to the design rather than working within the blueprint of how humans perceive and process the world around them. This practical guide explains how you can apply key principles in psychology to build products and experiences that are more intuitive and human-centered. Author Jon Yablonski deconstructs familiar apps and experiences to provide clear examples of how UX designers can build experiences that adapt to how users perceive and process digital interfaces.Youll learn:How aesthetically pleasing design creates positive responsesThe principles from psychology most useful for designersHow these psychology principles relate to UX heuristicsPredictive models including Fittss law, Jakobs law, and Hicks lawEthical implications of using psychology in designA framework for applying these principles

Cloud native security isn't a game for individual players. It requires team collaboration with a platform that can help cloud security engineers, developers, and operations people do their best work. That's what the cloud native application protection platform (CNAPP) delivers. With this practical guide, you'll learn how CNAPP can help you consolidate security through DevSecOps across cloud native technologies, practices, and application lifecycles. Through real-life attack scenarios, authors Russ Miles, Steve Giguere, and Taylor Smith help you explore how CNAPP not only mitigates multidimensional threats, but also reduces complexity and helps your team stay one step ahead of attackers. CNAPP provides a holistic approach to your cloud native development across identities, workloads, networks, and infrastructure. With this book, you will: Examine threats to different parts of the cloud native stack, including pipelines, supply chains, infrastructure, workloads, and applications Learn what CNAPP is and how it enables the context-sharing and collaboration necessary to secure your applications from development to runtime Assess your own attack surface from a code and runtime standpoint Identify blind spots in your existing cloud native security coverage Leverage CNAPP to achieve a holistic, collaborative security environment

With the massive adoption of microservices, operators and developers face far more complexity in their applications today. Service meshes can help you manage this problem by providing a unified control plane to secure, manage, and monitor your entire network. This practical guide shows you how the Linkerd service mesh enables cloud-native developers--including platform and site reliability engineers--to solve the thorny issue of running distributed applications in Kubernetes. Jason Morgan and Flynn draw on their years of experience at Buoyant--the creators of Linkerd--to demonstrate how this service mesh can help ensure that your applications are secure, observable, and reliable. You'll understand why Linkerd, the original service mesh, can still claim the lowest time to value of any mesh option available today. Learn how Linkerd works and which tasks it can help you accomplish Install and configure Linkerd in an imperative and declarative manner Secure interservice traffic and set up secure multicluster links Launch a zero trust authorization strategy in Kubernetes clusters Organize services in Linkerd to override error codes, set custom retries, and create timeouts Use Linkerd to manage progressive delivery and pair this service mesh with the ingress of your choice

Software as a service (SaaS) is on the path to becoming the de facto model for building, delivering, and operating software solutions. Adopting the multi-tenant model of SaaS requires builders to take on a broad range of new architecture, implementation, and operational challenges. How data is stored, how resources are isolated, how tenants are authenticated, how microservices are built--these are all examples of areas that builders must consider when designing and creating SaaS offerings. This practical book equips SaaS builders and architects with a collection of patterns, strategies, and insights to help you bridge these technical and business challenges. Tod Golding, a global SaaS lead at AWS, provides you with an end-to-end view of SaaS architecture and development techniques for addressing the unique blend of challenges associated with building a robust SaaS solution that realizes its full potential.

Decentralized finance (DeFi) is a rapidly growing field in fintech, having grown from $700 million to $100 billion over the past three years alone. But the lack of reliable information makes this area both risky and murky. In this practical book, experienced securities attorney Alexandra Damsker explains DeFi's role in both blockchain and finance. Ideal for developers looking to build decentralized applications (DApps), this book compares DeFi to traditional bank-led fintech and explains why DeFi is exploding in interest and popularity. You'll explore the growing array of DApps and platforms in various categories, including their benefits and drawbacks, and learn how DeFi tools work together from the perspective of both users and developers. With this book, you will: Learn how DeFi fits into the blockchain and fintech worlds Understand why it's important to move beyond the banking system Explore the tools for building a useful, functional DeFi application Learn the risks, benefits, regulatory concerns, and unresolved issues in this nascent and fast-growing industry See which technologies are well-positioned to be incorporated into DeFi blockchains in the near future Assess your own risk level to determine which strategies are most appropriate

Maverick Scientist is the memoir of Forrest Mims, who forged a distinguished scientific career despite having no academic training in science. Named one of the "50 Best Brains in Science" by Discover magazine, Forrest shares what sparked his childhood curiosity and relates a lifetime of improbable, dramatic, and occasionally outright dangerous experiences in the world of science. At thirteen he invented a new method of rocket control. At seventeen he designed and built an analog computer that could translate Russian into English and that the Smithsonian collected as an example of an early hobby computer. While majoring in government at Texas A&M University, Forrest created a hand-held, radar-like device to help guide the blind. And during his military service, he had to be given special clearance to do top secret laser research at the Air Force Weapons Lab. Why? Because while he lacked the required engineering degree, they wanted his outside-the-box thinking on the project. He went on to co-found MITS, Inc., producer of the first commercially successful personal computer, wrote a series of electronics books for Radio Shack that sold more than seven million copies, and designed the music synthesizer circuit that became known as the infamous Atari Punk Console. All this came before he started consulting for NASA's Goddard Space Flight Center, and NOAA's famous Mauna Loa Observatory, and earning the prestigious Rolex Award. This intimate portrait of a self-made scientist shares a revelatory look inside the scientific community, and tells the story of a lifelong learner who stood by his convictions even when pressured by the establishment to get in line with conventional wisdom. With dozens of personal photos and illustrations, Maverick Scientist serves as proof that to be a scientist, you simply need to do science.

With this book, Chris Fregly, Antje Barth, and Shelbee Eigenbrode from AWS help CTOs, ML practitioners, application developers, business analysts, data engineers, and data scientists find practical ways to use this exciting new technology.

乌龟提杰要跳。乌龟如何跳？。这个故事教我们 如何不停试验到成功。wū guī tí jié yào tiào 。 wū guī rú hé tiào ？ zhè ge gù shi jiào wǒ men rú hé bù tíng shì yàn dào chéng gōng 。 A Turtle named TJ wants to jump. How can a turtle jump? This story teaches us all how to keep trying until we succeed.

后记 "知更鸟的第一次飞行 "是要飞但怕飞的故事。 知更鸟克服恐惧并学会飞翔！这个寓言帮助我们每个人找到自己的翅膀。 "Robin's First Flight" is the story of wanting to fly but afraid to try. Robin overcomes fear and learns to soar! This fable helps each of us find our own wings.

Traditional data architecture patterns are severely limited. To use these patterns, you have to ETL data into each tool--a cost-prohibitive process for making warehouse features available to all of your data. The lack of flexibility with these patterns requires you to lock into a set of priority tools and formats, which creates data silos and data drift. This practical book shows you a better way. Apache Iceberg provides the capabilities, performance, scalability, and savings that fulfill the promise of an open data lakehouse. By following the lessons in this book, you'll be able to achieve interactive, batch, machine learning, and streaming analytics with this high-performance open source format. Authors Tomer Shiran, Jason Hughes, and Alex Merced from Dremio show you how to get started with Iceberg. With this book, you'll learn: The architecture of Apache Iceberg tables What happens under the hood when you perform operations on Iceberg tables How to further optimize Iceberg tables for maximum performance How to use Iceberg with popular data engines such as Apache Spark, Apache Flink, and Dremio Discover why Apache Iceberg is a foundational technology for implementing an open data lakehouse.

Gain the valuable skills and techniques you need to accelerate the delivery of machine learning solutions. With this practical guide, data scientists, ML engineers, and their leaders will learn how to bridge the gap between data science and Lean product delivery in a practical and simple way. David Tan, Ada Leung, and Dave Colls show you how to apply time-tested software engineering skills and Lean product delivery practices to reduce toil and waste, shorten feedback loops, and improve your team's flow when building ML systems and products. Based on the authors' experience across multiple real-world data and ML projects, the proven techniques in this book will help your team avoid common traps in the ML world, so you can iterate and scale more quickly and reliably. You'll learn how to overcome friction and experience flow when delivering ML solutions. You'll also learn how to: Write automated tests for ML systems, containerize development environments, and refactor problematic codebases Apply MLOps and CI/CD practices to accelerate experimentation cycles and improve reliability of ML solutions Apply Lean delivery and product practices to improve your odds of building the right product for your users Identify suitable team structures and intra- and inter-team collaboration techniques to enable fast flow, reduce cognitive load, and scale ML within your organization

If programming is magic then web scraping is surely a form of wizardry. By writing a simple automated program, you can query web servers, request data, and parse it to extract the information you need. The expanded edition of this practical book not only introduces you web scraping, but also serves as a comprehensive guide to scraping almost every type of data from the modern web.Part I focuses on web scraping mechanics: using Python to request information from a web server, performing basic handling of the servers response, and interacting with sites in an automated fashion. Part II explores a variety of more specific tools and applications to fit any web scraping scenario youre likely to encounter.Parse complicated HTML pagesDevelop crawlers with the Scrapy frameworkLearn methods to store data you scrapeRead and extract data from documentsClean and normalize badly formatted dataRead and write natural languagesCrawl through forms and loginsScrape JavaScript and crawl through APIsUse and write image-to-text softwareAvoid scraping traps and bot blockersUse scrapers to test your website

How can you make sense of the complex IoT landscape? With dozens of components ranging from devices to metadata about the devices, it's easy to get lost among the possibilities. But it's not impossible if you have the right guide to help you navigate all the complexities. This practical book shows developers, architects, and IT managers how to build IoT solutions on Azure. Author Blaize Stewart presents a comprehensive view of the IoT landscape. You'll learn about devices, device management at scale, and the tools Azure provides for building globally distributed systems. You'll also explore ways to organize data by choosing the appropriate dataflow and data storage technologies. The final chapters examine data consumption and solutions for delivering data to consumers with Azure. Get the architectural guidance you need to create holistic solutions with devices, data, and everything in between. This book helps you: Meet the demands of an IoT solution with Azure-provided functionality Use Azure to create complete scalable and secure IoT systems Understand how to articulate IoT architecture and solutions Guide conversations around common problems that IoT applications solve Select the appropriate technologies in the Azure space to build IoT applications

If you were handed two different but related sets of data, what tools would you use to find the matches? What if all you had was SQL SELECT access to a database? In this practical book, author Jim Lehmer provides best practices, techniques, and tricks to help you import, clean, match, score, and think about heterogeneous data using SQL. DBAs, programmers, business analysts, and data scientists will learn how to identify and remove duplicates, parse strings, extract data from XML and JSON, generate SQL using SQL, regularize data and prepare datasets, and apply data quality and ETL approaches for finding the similarities and differences between various expressions of the same data. Full of real-world techniques, the examples in the book contain working code. You'll learn how to: Identity and remove duplicates in two different datasets using SQL Regularize data and achieve data quality using SQL Extract data from XML and JSON Generate SQL using SQL to increase your productivity Prepare datasets for import, merging, and better analysis using SQL Report results using SQL Apply data quality and ETL approaches to finding similarities and differences between various expressions of the same data

This practical guide provides a collection of techniques and best practices that are generally overlooked in most data engineering and data science pedagogy. A common misconception is that great data scientists are experts in the "big themes" of the discipline--machine learning and programming. But most of the time, these tools can only take us so far. In practice, the smaller tools and skills really separate a great data scientist from a not-so-great one. Taken as a whole, the lessons in this book make the difference between an average data scientist candidate and a qualified data scientist working in the field. Author Daniel Vaughan has collected, extended, and used these skills to create value and train data scientists from different companies and industries. With this book, you will: Understand how data science creates value Deliver compelling narratives to sell your data science project Build a business case using unit economics principles Create new features for a ML model using storytelling Learn how to decompose KPIs Perform growth decompositions to find root causes for changes in a metric Daniel Vaughan is head of data at Clip, the leading paytech company in Mexico. He's the author of Analytical Skills for AI and Data Science (O'Reilly).

Explore the theory and practice of designing and writing serverless applications using examples from the Knative project. With this practical guide, mid-level to senior application developers and team managers will learn when and why to target serverless platforms when developing microservices or applications. Along the way, you'll also discover warning signs that suggest why serverless might cause you more trouble than joy. Drawing on author Evan Anderson's 15 years of experience developing and maintaining applications in the cloud--and more than six years of experience with serverless platforms at scale--this book acts as your guide into the high-velocity world of serverless application development. You'll come to appreciate why Knative is the most widely adopted open source serverless platform available. With this book, you will: Learn what serverless is, how it works, and why teams are adopting it Understand the benefits of Knative for cloud native development teams Learn how to build a serverless application on Knative Explore the challenges serverless introduces for debugging and the tools that can help improve it Learn why event-driven architecture and serverless compute are complementary but distinct Understand when a serverless approach might not be the right system design

"The adoption of serverless is on the rise, but until now, little guidance has been available for development teams that want to apply this technology on AWS. This definitive guide is packed with architectural, security, and data best practices and patterns for architects and engineers who want to build reliable enterprise-scale serverless solutions. Sheen Brisals, an AWS Serverless Hero, and Luke Hedger, an AWS Community Builder, outline the serverless adoption requirements for an enterprise, examine the development tools your team needs, and explain in depth the nuances of testing event-driven and distributed serverless services. You'll gain practical guidance for keeping up with change and learn how to build serverless solutions with sustainability in mind. Examine the serverless technology ecosystem and AWS services needed to develop serverless applications; learn the approach and preparation required for a successful serverless adoption in an enterprise; learn serverless architectures and implementation patterns; design, develop, and test distributed serverless microservices on AWS cloud; apply security best practices while building serverless solutions; identify and adapt the implementation patterns for your particular use case; incorporate the necessary measures for observable serverless applications; implement sustainable serverless applications in the cloud "--

Trillions of lines of code help us in our lives, companies, and organizations. But just a single software cybersecurity vulnerability can stop entire companies from doing business and cause billions of dollars in revenue loss and business recovery. Securing the creation and deployment of software, also known as software supply chain security, goes well beyond the software development process. This practical book gives you a comprehensive look at security risks and identifies the practical controls you need to incorporate into your end-to-end software supply chain. Author Cassie Crossley demonstrates how and why everyone involved in the supply chain needs to participate if your organization is to improve the security posture of its software, firmware, and hardware. With this book, you'll learn how to: Pinpoint the cybersecurity risks in each part of your organization's software supply chain Find the cybersecurity frameworks and resources that can improve security Identify the roles that participate in the supply chain--including IT, development, operations, manufacturing, and procurement Design initiatives and controls for each part of the supply chain using existing frameworks and references Evaluate third-party risk in your supply chain

Microservices can be a very effective approach for delivering value to your organization and to your customers. If you get them right, microservices help you to move fast, making changes to small parts of your system hundreds of times a day. But get them wrong and microservices just make everything more complicated. In this book, technical strategist Sarah Wells provides practical, in-depth advice for moving to microservices. Having built her first microservices architecture in 2013 for the Financial Times, Sarah discusses the approaches you need to take from the start, and explains the potential traps most likely to trip you up. You'll also learn how to maintain the architecture as your systems mature while minimizing the time you spend on support and maintenance. With this book, you will: Learn the impact of microservices on software development patterns and practices Identify the organizational changes you need to make to successfully build and operate this architecture Determine the steps you must take before you move to microservices Understand the traps to avoid when you create a microservices architecture--and learn how to recover if you fall into one

Kubernetes is becoming the de-facto standard for container orchestration and distributed applications management across a microservices framework. With this practical cookbook, youll learn hands-on recipes for automating the deployment, scaling, and operations of application containers across clusters of hosts.The book's easy-lookup problem-solution-discussion format helps you find the detailed answers you needquickly. Kubernetes lets you deploy your applications quickly and predictably, so you can efficiently respond to customer demand. This cookbook, ideal for developers and system administers alike, provides the essential knowledge you need to get there.Youll find recipes for:Kubernetes installationKubernetes API, API groupsApplication primitivesMonitoringTroubleshooting

Implementing and designing systems that make suggestions to users are among the most popular and essential machine learning applications available. Whether you want customers to find the most appealing items at your online store, videos to enrich and entertain them, or news they need to know, recommendation systems (RecSys) provide the way. In this practical book, authors Bryan Bischof and Hector Yee illustrate the core concepts and examples to help you create a RecSys for any industry or scale. You'll learn the math, ideas, and implementation details you need to succeed. This book includes the RecSys platform components, relevant MLOps tools in your stack, plus code examples and helpful suggestions in PySpark, SparkSQL, FastAPI, Weights & Biases, and Kafka. You'll learn: The data essential for building a RecSys How to frame your data and business as a RecSys problem Ways to evaluate models appropriate for your system Methods to implement, train, test, and deploy the model you choose Metrics you need to track to ensure your system is working as planned How to improve your system as you learn more about your users, products, and business case

All cloud architects need to know how to build data platforms that enable businesses to make data-driven decisions and deliver enterprise-wide intelligence in a fast and efficient way. This handbook shows you how to design, build, and modernize cloud native data and machine learning platforms using AWS, Azure, Google Cloud, and multicloud tools like Snowflake and Databricks. Authors Marco Tranquillin, Valliappa Lakshmanan, and Firat Tekiner cover the entire data lifecycle from ingestion to activation in a cloud environment using real-world enterprise architectures. You'll learn how to transform, secure, and modernize familiar solutions like data warehouses and data lakes, and you'll be able to leverage recent AI/ML patterns to get accurate and quicker insights to drive competitive advantage. You'll learn how to: Design a modern and secure cloud native or hybrid data analytics and machine learning platform Accelerate data-led innovation by consolidating enterprise data in a governed, scalable, and resilient data platform Democratize access to enterprise data and govern how business teams extract insights and build AI/ML capabilities Enable your business to make decisions in real time using streaming pipelines Build an MLOps platform to move to a predictive and prescriptive analytics approach

What sets Laravel apart from other PHP web frameworks? Speed and simplicity, for starters. This rapid application development framework and its vast ecosystem of tools let you quickly build new sites and applications with clean, readable code. Fully updated to cover Laravel 5.8, the latest release, the second edition of this practical guide provides the definitive introduction to one of todays most popular web frameworks.Matt Stauffera leading teacher and developer in the Laravel communitydelivers a high-level overview and concrete examples to help experienced PHP web developers get started with Laravel right away. By the time you reach the last page, you should feel comfortable writing an entire application in Laravel from scratch.

"Cyber risk management is one of the most urgent issues facing enterprises today. This book presents a detailed framework for designing, developing, and implementing a cyber risk management program that addresses your company's specific needs. Ideal for corporate directors, senior executives, security risk practitioners, and auditors at many levels, this guide offers both the strategic insight and tactical guidance you're looking for."--Publisher's description.

"Join the technological revolution that's taking the financial world by storm. Mastering Bitcoin is your guide through the seemingly complex world of Bitcoin, providing the knowledge you need to participate in the internet of money. Whether you're building the next killer app, investing in a startup, or simply curious about the technology, this revised and expanded third edition provides essential detail to get you started. Bitcoin, the first successful decentralized digital currency, has already spawned a multibillion-dollar global economy open to anyone with the knowledge and passion to participate. Mastering Bitcoin provides the knowledge. You supply the passion" --

"This practical book shows you how to ensure that the data your organization relies on is trustworthy ... [and] explain[s] how you can use automated data quality monitoring to cover all your tables efficiently, proactively alert on issues, and resolve problems immediately"--

As tech products become more prevalent today, the demand for machine learning professionals continues to grow. But the responsibilities and skill sets required of ML professionals still vary drastically from company to company, making the interview process difficult to predict. In this guide, data science leader Susan Shu Chang shows you how to tackle the ML hiring process. Having served as principal data scientist in several companies, Chang has considerable experience as both ML interviewer and interviewee. She'll take you through the highly selective recruitment process by sharing hard-won lessons she learned along the way. You'll quickly understand how to successfully navigate your way through typical ML interviews. This guide shows you how to: Explore various machine learning roles, including ML engineer, applied scientist, data scientist, and other positions Assess your interests and skills before deciding which ML role(s) to pursue Evaluate your current skills and close any gaps that may prevent you from succeeding in the interview process Acquire the skill set necessary for each machine learning role Ace ML interview topics, including coding assessments, statistics and machine learning theory, and behavioral questions Prepare for interviews in statistics and machine learning theory by studying common interview questions

Looking for quick answers for using C# 12? This tightly focused and practical guide tells you exactly what you need to know without long intros or bloated samples. Succinct and easy to browse, this pocket reference is an ideal quick source of information. If you know Java, C++, or an earlier C# version, this guide will help you get rapidly up to speed. All programs and code snippets are available as interactive samples in LINQPad. You can edit these samples and instantly see the results without needing to set up projects in Visual Studio.

With the shift from data warehouses to data lakes, data now lands in repositories before it's been transformed, enabling engineers to model raw data into clean, well-defined datasets. dbt (data build tool) helps you take data further. This practical book shows data analysts, data engineers, BI developers, and data scientists how to create a true self-service transformation platform through the use of dynamic SQL. Authors Rui Machado from Monstarlab and Hélder Russa from Jumia show you how to quickly deliver new data products by focusing more on value delivery and less on architectural and engineering aspects. If you know your business well and have the technical skills to model raw data into clean, well-defined datasets, you'll learn how to design and deliver data models without any technical influence. With this book, you'll learn: What dbt is and how a dbt project is structured How dbt fits into the data engineering and analytics worlds How to collaborate on building data models The main tools and architectures for building useful, functional data models How to fit dbt into data warehousing and laking architecture How to build tests for data transformations