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CRM Analytics, formerly known as Tableau CRM and Einstein Analytics, is a powerful and versatile data analytics platform that enables organizations to extract, combine, transform, and visualize their data to create valuable business insights.Creating Actionable Insights Using CRM Analytics provides a hands-on approach to CRM Analytics implementation and associated methodologies that will have you up and running and productive in no time. The book provides you with detailed explanations of essential concepts to help you to gain confidence and become competent in using the CRM Analytics platform for data extraction, combination, transformation, visualization, and action. As you make progress, you'll understand what CRM Analytics is and where it provides business value. You'll also learn how to bring your data together in CRM Analytics, build datasets and lenses for data analysis, create effective analytics dashboards for visualization and consumption by end users, and build dashboard actions that take the user from data to insight to action with ease.By the end of this book, you'll be able to solve business problems using CRM Analytics and design, build, test, and deploy analytics dashboards efficiently.
Sebastian Raschka, Yuxi (Hayden) Liu, Vahid Mirjalili, Dmytro Dzhulgakov
Machine Learning with PyTorch and Scikit-Learn is a comprehensive guide to machine learning and deep learning with PyTorch. It acts as both a step-by-step tutorial and a reference you'll keep coming back to as you build your machine learning systems.Packed with clear explanations, visualizations, and examples, the book covers all the essential machine learning techniques in depth. While some books teach you only to follow instructions, with this machine learning book, we teach the principles allowing you to build models and applications for yourself.Why PyTorch?PyTorch is the Pythonic way to learn machine learning, making it easier to learn and simpler to code with. This book explains the essential parts of PyTorch and how to create models using popular libraries, such as PyTorch Lightning and PyTorch Geometric.You will also learn about generative adversarial networks (GANs) for generating new data and training intelligent agents with reinforcement learning. Finally, this new edition is expanded to cover the latest trends in deep learning, including graph neural networks and large-scale transformers used for natural language processing (NLP).This PyTorch book is your companion to machine learning with Python, whether you're a Python developer new to machine learning or want to deepen your knowledge of the latest developments.
Managing Data as a Product. Design and build data-product-centered socio-technical architectures
Traditional monolithic data platforms struggle with scalability and burden central data teams with excessive cognitive load, leading to challenges in managing technological debt. As maintenance costs escalate, these platforms lose their ability to provide sustained value over time. With two decades of hands-on experience implementing data solutions and his pioneering work in the Open Data Mesh Initiative, Andrea Gioia brings practical insights and proven strategies for transforming how organizations manage their data assets.Managing Data as a Product introduces a modular and distributed approach to data platform development, centered on the concept of data products. In this book, you’ll explore the rationale behind this shift, understand the core features and structure of data products, and learn how to identify, develop, and operate them in a production environment. The book guides you through designing and implementing an incremental, value-driven strategy for adopting data product-centered architectures, including strategies for securing buy-in from stakeholders. Additionally, it explores data modeling in distributed environments, emphasizing its crucial role in fully leveraging modern generative AI solutions.By the end of this book, you’ll have gained a comprehensive understanding of product-centric data architecture and the essential steps needed to adopt this modern approach to data management.
Leondra R. Gonzalez, Aaren Stubberfield, Angela Baltes
The data science job market is saturated with professionals of all backgrounds, including academics, researchers, bootcampers, and Massive Open Online Course (MOOC) graduates. This poses a challenge for companies seeking the best person to fill their roles. At the heart of this selection process is the data science interview, a crucial juncture that determines the best fit for both the candidate and the company.Cracking the Data Science Interview provides expert guidance on approaching the interview process with full preparation and confidence. Starting with an introduction to the modern data science landscape, you’ll find tips on job hunting, resume writing, and creating a top-notch portfolio. You’ll then advance to topics such as Python, SQL databases, Git, and productivity with shell scripting and Bash. Building on this foundation, you'll delve into the fundamentals of statistics, laying the groundwork for pre-modeling concepts, machine learning, deep learning, and generative AI. The book concludes by offering insights into how best to prepare for the intensive data science interview.By the end of this interview guide, you’ll have gained the confidence, business acumen, and technical skills required to distinguish yourself within this competitive landscape and land your next data science job.
Professionals working in the mobile forensics industry will be able to put their knowledge to work with this practical guide to learning how to extract and analyze all available data from an iOS device.This audiobook is a comprehensive, how-to guide that leads investigators through the process of collecting mobile devices and preserving, extracting, and analyzing data, as well as building a report. Complete with step-by-step explanations of essential concepts, practical examples, and self-assessment questions, this book starts by covering the fundamentals of mobile forensics and how to overcome challenges in extracting data from iOS devices. Once you've walked through the basics of iOS, you’ll learn how to use commercial tools to extract and process data and manually search for artifacts stored in database files. Next, you'll find out the correct workflows for handling iOS devices and understand how to extract valuable information to track device usage. You’ll also get to grips with analyzing key artifacts, such as browser history, the pattern of life data, location data, and social network forensics.By the end of this audiobook, you'll be able to establish a proper workflow for handling iOS devices, extracting all available data, and analyzing it to gather precious insights that can be reported as prosecutable evidence.
Franck Cornu, Anoop T., Vesa Juvonen
The SharePoint Framework (SPFx) has revolutionized how developers create custom solutions for Microsoft 365. Whether you're building Web Parts, extensions, or full-fledged applications, mastering SPFx is essential for delivering modern and scalable SharePoint solutions.Authored by experienced SPFx developers, this book serves as a comprehensive guide to developing with SPFx, offering practical examples, structured guidance, and best practices. You’ll start by understanding the Microsoft SharePoint and Microsoft 365 ecosystem before exploring hands-on development with SPFx. You’ll learn how to create Web Parts, work with the property pane, connect to APIs, deploy solutions, and implement different types of extensions. Additionally, the book covers debugging, testing, and upgrading solutions efficiently.By the end of this book, you’ll be able to confidently build, deploy, and manage SharePoint solutions using SPFx while leveraging community tools and libraries to enhance development efficiency.