Название: Essential Statistics for Data Science: A Concise Crash Course
Автор: Mu Zhu
Издательство: Oxford University Press
Год: 2023
Страниц: 177
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB

Essential Statistics for Data Science: A Concise Crash Course is for students entering a serious graduate program or advanced undergraduate teaching in data science without knowing enough statistics. The three part text introduces readers to the basics of probability and random variables and guides them towards relatively advanced topics in both frequentist and Bayesian in a matter of weeks.Part I, Talking Probability explains the statistical approach to analysing data with a probability model to describe the data generating process. Part II, Doing Statistics demonstrates how the unknown quantities in data i.e. it's parameters is applicable in statistical interference. Part III, Facing Uncertainty explains the importance of explicity describing how much uncertainty is caused by parameters with intrinsic scientific meaning and how to take that intoaccount when making decisions.Essential Statistics for Data Science: A Concise Crash Course provides an in-depth introduction for beginners, while being more focused than a typical undergraduate text, but still lighter and more accessible than an average graduate text. At the frontier of statistics, Data Science, or Machine Learning, the probability models used to describe the data-generating process can be pretty complex.

Название: Designing Data Governance from the Ground Up: Six Steps to Build a Data-Driven Culture
Автор: Lauren Maffeo
Издательство: Pragmatic Bookshelf
Год: January 2023 (Version: P1.0)
Страниц: 191
Язык: английский
Формат: pdf, epub, mobi
Размер: 10.2 MB

Businesses own more data than ever before, but it’s of no value if you don’t know how to use it. Data governance manages the people, processes, and strategy needed for deploying data projects to production. But doing it well is far from easy: Less than one fourth of business leaders say their organizations are data driven. In Designing Data Governance from the Ground Up, you’ll build a cross-functional strategy to create roadmaps and stewardship for data-focused projects, embed data governance into your engineering practice, and put processes in place to monitor data after deployment. In the last decade, the amount of data people produced grew 3,000 percent. Most organizations lack the strategy to clean, collect, organize, and automate data for production-ready projects. Without effective data governance, most businesses will keep failing to gain value from the mountain of data that’s available to them. There’s a plethora of content intended to help DataOps and DevOps teams reach production, but 90 percent of projects trained with Big Data fail to reach production because they lack governance.

Название: Data Mining: Concepts and Techniques, 4th Edition
Автор: Jiawei Han, Jian Pei, Hanghang Tong
Издательство: Morgan Kaufmann/Elsevier
Год: 2023
Страниц: 786
Язык: английский
Формат: pdf (true)
Размер: 19.4 MB

Data Mining: Concepts and Techniques, Fourth Edition introduces concepts, principles, and methods for mining patterns, knowledge, and models from various kinds of data for diverse applications. Specifically, it delves into the processes for uncovering patterns and knowledge from massive collections of data, known as knowledge discovery from data , or KDD . It focuses on the feasibility, usefulness, effectiveness, and scalability of data mining techniques for large data sets. After an introduction to the concept of data mining, the authors explain the methods for preprocessing, characterizing, and warehousing data. They then partition the data mining methods into several major tasks, introducing concepts and methods for mining frequent patterns, associations, and correlations for large data sets; data classificcation and model construction; cluster analysis; and outlier detection. Concepts and methods for deep learning are systematically introduced as one chapter. Finally, the book covers the trends, applications, and research frontiers in data mining.

Название: Exam Ref PL-900 Microsoft Power Platform Fundamentals, 2nd Edition
Автор: Craig Zacker
Издательство: Microsoft Press/Pearson Education
Год: 2023
Страниц: 389
Язык: английский
Формат: epub
Размер: 29.6 MB

Prepare for Microsoft Exam PL-900.Demonstrate your real-world knowledge of the fundamentals of Microsoft Power Platform, including its business value, core components, and the capabilities and advantages of Power BI, Power Apps, Power Automate, and Power Virtual Agents. Designed for business users, functional consultants, and other professionals, this Exam Ref focuses on the critical thinking and decision-making acumen needed for success at the Microsoft Certified: Power Platform Fundamentals level. Microsoft Power Platform is a collection of tools that are designed to simplify the process of gathering, processing, and reporting company data.

Название: Azure SQL Hyperscale Revealed: High-performance Scalable Solutions for Critical Data Workloads
Автор: Zoran Barac, Daniel Scott-Raynsford
Издательство: Apress
Год: 2023
Страниц: 459
Язык: английский
Формат: pdf
Размер: 29.1 MB

Take a deep dive into the Azure SQL Database Hyperscale Service Tier and discover a new form of cloud architecture from Microsoft that supports massive databases. The new horizontally scalable architecture, formerly code-named Socrates, allows you to decouple compute nodes from storage layers. This radically different approach dramatically increases the scalability of the service. This book shows you how to leverage Hyperscale to provide next-level scalability, high throughput, and fast performance from large databases in your environment. The book begins by showing how Hyperscale helps you eliminate many of the problems of traditional high-availability and disaster recovery architecture. You’ll learn how Hyperscale overcomes storage capacity limitations and issues with scale-up times and costs. With Hyperscale, your costs do not increase linearly with database size and you can manage more data than ever at a lower cost.

Название: Windows Everywhere : The rise and fall of the most important software platform of all time
Автор: Paul Thurrott, Rafael Rivera
Издательство: Leanpub
Год: 2023-03-19
Страниц: 938
Язык: английский
Формат: pdf (true)
Размер: 139.7 MB

This is the story of Microsoft Windows, but told in a different way and from a different perspective. It is the story of the aspirations that Microsoft had for the platform over time. Object-Oriented Programming in the era of “Cairo.” The brief moment when the .NET craze engulfed the company. The touch-first mania of Windows 8. And so much more. The history of Windows can be seen as a series of reactions to competitors, market trends, and internal forces that were seeking change. Along the way, Microsoft worked to improve and adapt Windows to an incredible variety of new uses cases, form factors, and competition. From a milestone perspective, most normally think of the history of Windows as a series of product version releases starting in 1985. That history is well-documented, I think, but since it’s important to our alternate history of application development technologies, it’s perhaps worth considering briefly.

Название: Guide to Teaching Data Science: An Interdisciplinary Approach
Автор: Orit Hazzan, Koby Mike
Издательство: Springer
Год: 2023
Страниц: 330
Язык: английский
Формат: pdf (true), epub
Размер: 15.8 MB

Data Science is a new discipline of research that is gaining growing interest in both industry and academia. As a result, demand is increasing for Data Science programs for a variety of learners from a variety of disciplines (Data Science, Computer Science, statistics, engineering, life science, social science and humanities) and a variety of levels (from school children to academia and industry). While significant efforts are being invested in the development of Data Science curricula, or in other words, in what to teach, only sporadic discussions focus today on the Data Science pedagogy, that is, on how to teach. This is the focus of this guide. This book provides a variety of pedagogical discussions and specific teaching methods and frameworks, as well as includes exercises, and guidelines related to many Data Science concepts (e.g., data thinking and the Data Science workflow), main Machine Learning algorithms and concepts (e.g., KNN, SVM, Neural Networks, performance metrics, confusion matrix, and biases) and Data Science professional topics.

Название: Chromebook For Dummies, 3rd Edition
Автор: Peter H. Gregory
Издательство: For Dummies
Год: 2023
Страниц: 483
Язык: английский
Формат: pdf (true)
Размер: 36.79 MB

The return of the bestselling Chromebook guide on the market. Chromebook For Dummies, Third Edition, is your easy-to-follow guide to the low-cost alternative to a traditional laptop. This beginner’s manual walks you through setting up your Chromebook, transitioning from using a traditional computer, and customizing the system to fit your needs. In case you’re wondering, the Chromebook can be used for anything you'd normally do online―checking email, browsing websites, watching videos. This book takes you through all of it, giving you the latest updates on new Chromebook hardware and software features. Navigate apps, apply advanced settings and features, and turn to this guide time and again as you customize and optimize your Chromebook’s performance. New and novice Chromebook users will love this approachable intro to Google’s little portable computer.

Название: The Service-Oriented Enterprise: Learn Enterprise Architecture and Its Viable Services
Автор: Tom Graves
Издательство: Apress
Год: 2023
Страниц: 242
Язык: английский
Формат: pdf (true), epub
Размер: 10.1 MB

A service-oriented architecture is fundamental to many new IT applications, from web development to social software and cloud computing. The same principles can be applied to every aspect of the service-oriented enterprise – not just in IT. In this book, you’ll explore how an enterprise architecture and viable services can link together to create a simpler yet far more powerful view of the enterprise, as a dynamic, unified whole. You can use the ideas, principles and methods described here in business transformation, workflow mapping, system design and much else besides, in every type of enterprise - including those in which there may be little or no IT at all. Step by step, you’ll walk through the basics of service-oriented architectures, the four key categories of services and how they connect, and how all of this comes together in real-world service design, implementation and operations. By the end of this book, you’ll learn how to construct function models and service models of your enterprise as a base for service-mapping, and how to pinpoint and map the information flows you need for service-management and service-performance, to keep everything on-track to purpose.

Название: Practical Data Mesh: Building Decentralized Data Architectures with Event Streams
Автор: Adam Bellemare
Издательство: Confluent, Inc.
Год: 2022
Язык: английский
Формат: pdf (true)
Размер: 10.9 MB

What Is Data Mesh? Data mesh is a concept that ensures data access, governance, federation, and interoperability across distributed teams and systems. It is a new approach for designing modern data architectures, based on four principles. The software industry has always been susceptible to trends. Some stick, some pass, but all vie for the limelight in one way or another. Agile, SOA, cloud, data lakes, microservices, DevOps, and event streaming have all had a fundamental effect on the software we build today. Data mesh may well be the next innovation we can add to this list. I see it as a kind of microservices for data architecture. Part technology and part practice, this socio-technical theory aims to let large, interconnected organizations avoid putting all their data into one single place: a pattern that can lead to paralysis. In a data mesh, different applications, pipelines, databases, storage layers, etc., are instead connected through self-service data products, creating a network, or “mesh,” of data that has no central point where teams are forced to wait in line or step on each other’s toes. Such problems plague the monolithic application and the monolithic data warehouse alike.