Publisher: Packt Publishing
Abirami Sukumaran, Priyanka Vergadia, Bagirathi Narayanan
In the age of lightning-speed delivery, customers want everything developed, built, and delivered at high speed and at scale. Knowledge, design, and choice of database is critical in that journey, but there is no one-size-fits-all solution. This book serves as a comprehensive and practical guide for data professionals who want to design and model their databases efficiently. The book begins by taking you through business, technical, and design considerations for databases. Next, it takes you on an immersive structured database deep dive for both transactional and analytical real-world use cases using Cloud SQL, Spanner, and BigQuery. As you progress, you’ll explore semi-structured and unstructured database considerations with practical applications using Firestore, cloud storage, and more. You’ll also find insights into operational considerations for databases and the database design journey for taking your data to AI with Vertex AI APIs and generative AI examples. By the end of this book, you will be well-versed in designing and modeling data and databases for your applications using Google Cloud.
Alkin Tezuysal, Ibrar Ahmed, Peter Zaitsev
Database Design and Modeling with PostgreSQL and MySQL will equip you with the knowledge and skills you need to architect, build, and optimize efficient databases using two of the most popular open-source platforms.As you progress through the chapters, you'll gain a deep understanding of data modeling, normalization, and query optimization, supported by hands-on exercises and real-world case studies that will reinforce your learning. You'll explore topics like concurrency control, backup and recovery strategies, and seamless integration with web and mobile applications. These advanced topics will empower you to tackle complex database challenges confidently and effectively. Additionally, you’ll explore emerging trends, such as NoSQL databases and cloud-based solutions, ensuring you're well-versed in the latest developments shaping the database landscape. By embracing these cutting-edge technologies, you'll be prepared to adapt and innovate in today's ever-evolving digital world.By the end of this book, you’ll be able to understand the technologies that exist to design a modern and scalable database for developing web applications using MySQL and PostgreSQL open-source databases.
Saba Shah, Rod Waltermann
Spark has become a de facto standard for big data processing. Migrating data processing to Spark saves resources, streamlines your business focus, and modernizes workloads, creating new business opportunities through Spark’s advanced capabilities. Written by a senior solutions architect at Databricks, with experience in leading data science and data engineering teams in Fortune 500s as well as startups, this book is your exhaustive guide to achieving the Databricks Certified Associate Developer for Apache Spark certification on your first attempt.You’ll explore the core components of Apache Spark, its architecture, and its optimization, while familiarizing yourself with the Spark DataFrame API and its components needed for data manipulation. You’ll also find out what Spark streaming is and why it’s important for modern data stacks, before learning about machine learning in Spark and its different use cases. What’s more, you’ll discover sample questions at the end of each section along with two mock exams to help you prepare for the certification exam.By the end of this book, you’ll know what to expect in the exam and gain enough understanding of Spark and its tools to pass the exam. You’ll also be able to apply this knowledge in a real-world setting and take your skillset to the next level.
Stephanie Rivera, Anastasia Prokaieva, Amanda Baker, Hayley...
Discover what makes the Databricks Data Intelligence Platform the go-to choice for top-tier machine learning solutions. Written by a team of industry experts at Databricks with decades of combined experience in big data, machine learning, and data science, Databricks ML in Action presents cloud-agnostic, end-to-end examples with hands-on illustrations of executing data science, machine learning, and generative AI projects on the Databricks Platform.You’ll develop expertise in Databricks' managed MLflow, Vector Search, AutoML, Unity Catalog, and Model Serving as you learn to apply them practically in everyday workflows. This Databricks book not only offers detailed code explanations but also facilitates seamless code importation for practical use. You’ll discover how to leverage the open-source Databricks platform to enhance learning, boost skills, and elevate productivity with supplemental resources.By the end of this book, you'll have mastered the use of Databricks for data science, machine learning, and generative AI, enabling you to deliver outstanding data products.
Alejandro Duarte
Vaadin is an open-source Java framework used to build modern user interfaces. Vaadin 8 simplifies application development and improves user experience. The book begins with an overview of the architecture of Vaadin applications and the way you can organize your code in modules.Then it moves to the more advanced topics about advanced topics such as internationalization, authentication, authorization, and database connectivity. The book also teaches you how to implement CRUD views, how to generate printable reports, and how to manage data with lazy loading.By the end of this book you will be able to architect, implement, and deploy stunning Vaadin applications, and have the knowledge to master web development with Vaadin.
Jonas Christensen, Nakul Bajaj, Manmohan Gosada, Kirk...
In the rapidly advancing data-driven world where data quality is pivotal to the success of machine learning and artificial intelligence projects, this critically timed guide provides a rare, end-to-end overview of data-centric machine learning (DCML), along with hands-on applications of technical and non-technical approaches to generating deeper and more accurate datasets.This book will help you understand what data-centric ML/AI is and how it can help you to realize the potential of ‘small data’. Delving into the building blocks of data-centric ML/AI, you’ll explore the human aspects of data labeling, tackle ambiguity in labeling, and understand the role of synthetic data. From strategies to improve data collection to techniques for refining and augmenting datasets, you’ll learn everything you need to elevate your data-centric practices. Through applied examples and insights for overcoming challenges, you’ll get a roadmap for implementing data-centric ML/AI in diverse applications in Python.By the end of this book, you’ll have developed a profound understanding of data-centric ML/AI and the proficiency to seamlessly integrate common data-centric approaches in the model development lifecycle to unlock the full potential of your machine learning projects by prioritizing data quality and reliability.
Thomas Kurian Theakanath
Datadog is an essential cloud monitoring and operational analytics tool which enables the monitoring of servers, virtual machines, containers, databases, third-party tools, and application services. IT and DevOps teams can easily leverage Datadog to monitor infrastructure and cloud services, and this book will show you how.The book starts by describing basic monitoring concepts and types of monitoring that are rolled out in a large-scale IT production engineering environment. Moving on, the book covers how standard monitoring features are implemented on the Datadog platform and how they can be rolled out in a real-world production environment. As you advance, you'll discover how Datadog is integrated with popular software components that are used to build cloud platforms. The book also provides details on how to use monitoring standards such as Java Management Extensions (JMX) and StatsD to extend the Datadog platform. Finally, you'll get to grips with monitoring fundamentals, learn how monitoring can be rolled out using Datadog proactively, and find out how to extend and customize the Datadog platform.By the end of this Datadog book, you will have gained the skills needed to monitor your cloud infrastructure and the software applications running on it using Datadog.
Data-oriented Development with AngularJS
Manoj Waikar, Manoj M Waikar
Greg Deckler
DAX provides an extra edge by extracting key information from the data that is already present in your model. Filled with examples of practical, real-world calculations geared toward business metrics and key performance indicators, this cookbook features solutions that you can apply for your own business analysis needs.You'll learn to write various DAX expressions and functions to understand how DAX queries work. The book also covers sections on dates, time, and duration to help you deal with working days, time zones, and shifts. You'll then discover how to manipulate text and numbers to create dynamic titles and ranks, and deal with measure totals. Later, you'll explore common business metrics for finance, customers, employees, and projects. The book will also show you how to implement common industry metrics such as days of supply, mean time between failure, order cycle time and overall equipment effectiveness. In the concluding chapters, you'll learn to apply statistical formulas for covariance, kurtosis, and skewness. Finally, you'll explore advanced DAX patterns for interpolation, inverse aggregators, inverse slicers, and even forecasting with a deseasonalized correlation coefficient.By the end of this book, you'll have the skills you need to use DAX's functionality and flexibility in business intelligence and data analytics.
DAX for Humans. The No CALCULATE Guide that Makes DAX Easy
Greg Deckler
Although DAX has been around for over a decade, many struggle to master the language primarily because DAX is often taught through the CALCULATE function, which is the most complex and unintuitive function in all of DAX. But what if DAX could be taught without CALCULATE? The result would be an incredibly intuitive and easy way to learn DAX.DAX for Humans stands the traditional approach to learning DAX on its head, foregoing the traditional, legacy methods of learning DAX for a more modern approach that focuses on core DAX concepts and not any specific function. Even if you know nothing about DAX, from the very first chapter you will learn the essentials of the DAX language, as well as a single pattern to solve the majority of DAX problems. From that point forward, you’ll explore how to work with the basic building blocks of the DAX language and apply what you learn to real-world business scenarios across customers, human resources, projects, finance, operations, and more.By the end of this book, you’ll be able to apply your DAX skills to simple, complex, and advanced scenarios; understand how to optimize and debug your DAX code; and even know how to efficiently apply artificial intelligence to help you write and debug your DAX code.
Ali Madani
Debugging Machine Learning Models with Python is a comprehensive guide that navigates you through the entire spectrum of mastering machine learning, from foundational concepts to advanced techniques. It goes beyond the basics to arm you with the expertise essential for building reliable, high-performance models for industrial applications. Whether you're a data scientist, analyst, machine learning engineer, or Python developer, this book will empower you to design modular systems for data preparation, accurately train and test models, and seamlessly integrate them into larger technologies.By bridging the gap between theory and practice, you'll learn how to evaluate model performance, identify and address issues, and harness recent advancements in deep learning and generative modeling using PyTorch and scikit-learn. Your journey to developing high quality models in practice will also encompass causal and human-in-the-loop modeling and machine learning explainability. With hands-on examples and clear explanations, you'll develop the skills to deliver impactful solutions across domains such as healthcare, finance, and e-commerce.
Alexandru Bolboacă, Ferenc-Lajos Deák
Think you know C++? Think again.For decades, C++ has been clouded by myths and misunderstandings—from its early design decisions to misconceptions that still linger today. Claims like C++ is too hard to learn or C++ is obsolete are often rooted in some truth, but they are outdated and fail to capture the language’s ongoing evolution and modern capabilities.Written by industry veterans with over 40 years of combined experience, this book uncovers the myths, exploring their origins and relevance in the context of today’s C++ landscape. It equips you with a deeper understanding of advanced features and best practices to elevate your projects. Each chapter tackles a specific misconception, shedding light on C++'s modern features, such as smart pointers, lambdas, and concurrency. You’ll learn practical strategies to navigate common challenges like code portability and compiler compatibility, as well as how to incorporate modern best practices into your C++ codebase to optimize performance and future-proof your projects. By the end of this book, you’ll have a comprehensive understanding of C++'s evolution, equipping you to make informed decisions and harness its powerful features to enhance your skills, coding practices, and projects.
Rohan Pinto
Looking forward to mastering digital identity? This book will help you get to grips with complete frameworks, tools, and strategies for safeguarding personal data, securing online transactions, and ensuring trust in digital interactions in today's cybersecurity landscape.Decentralized Identity Explained delves into the evolution of digital identities, from their historical roots to the present landscape and future trajectories, exploring crucial concepts such as IAM, the significance of trust anchors and sources of truth, and emerging trends such as SSI and DIDs. Additionally, you’ll gain insights into the intricate relationships between trust and risk, the importance of informed consent, and the evolving role of biometrics in enhancing security within distributed identity management systems. Through detailed discussions on protocols, standards, and authentication mechanisms, this book equips you with the knowledge and tools needed to navigate the complexities of digital identity management in both current and future cybersecurity landscapes.By the end of this book, you’ll have a detailed understanding of digital identity management and best practices to implement secure and efficient digital identity frameworks, enhancing both organizational security and user experiences in the digital realm.
Dorothy R. Kirk
Even though object-oriented software design enables more easily maintainable code, companies choose C++ as an OO language for its speed. Object-oriented programming in C++ is not automatic – it is crucial to understand OO concepts and how they map to both C++ language features and OOP techniques. Distinguishing your code by utilizing well-tested, creative solutions, which can be found in popular design patterns, is crucial in today’s marketplace. This book will help you to harness OOP in C++ to write better code.Starting with the essential C++ features, which serve as building blocks for the key chapters, this book focuses on explaining fundamental object-oriented concepts and shows you how to implement them in C++. With the help of practical code examples and diagrams, you’ll learn how and why things work. The book’s coverage furthers your C++ repertoire by including templates, exceptions, operator overloading, STL, and OO component testing. You’ll discover popular design patterns with in-depth examples and understand how to use them as effective programming solutions to solve recurring OOP problems.By the end of this book, you’ll be able to employ essential and advanced OOP concepts to create enduring and robust software.
Irena Cronin
Ever wondered how large language models (LLMs) work and how they're shaping the future of artificial intelligence? Written by a renowned author and AI, AR, and data expert, Decoding Large Language Models is a combination of deep technical insights and practical use cases that not only demystifies complex AI concepts, but also guides you through the implementation and optimization of LLMs for real-world applications.You’ll learn about the structure of LLMs, how they're developed, and how to utilize them in various ways. The chapters will help you explore strategies for improving these models and testing them to ensure effective deployment. Packed with real-life examples, this book covers ethical considerations, offering a balanced perspective on their societal impact. You’ll be able to leverage and fine-tune LLMs for optimal performance with the help of detailed explanations. You’ll also master techniques for training, deploying, and scaling models to be able to overcome complex data challenges with confidence and precision. This book will prepare you for future challenges in the ever-evolving fields of AI and NLP.By the end of this book, you’ll have gained a solid understanding of the architecture, development, applications, and ethical use of LLMs and be up to date with emerging trends, such as GPT-5.
Monika Mathe, Monika Math?É?íÂ!(C)
osCommerce has been around since March 2000. At present there are over 10,000 live, registered osCommerce sites, and about 100,000 registered community members. Apart from providing ready-made solutions to problems, as well as a huge repository of information, the osCommerce community is a living entity with which we can all interact. With the rising success and popularity of this remarkable piece of software, things can only get better.