Showing titles in Data Science

Author Martin Kleppmann helps you navigate the diverse data landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. 

Statistics has played a leading role in our scientific understanding of the world for centuries, yet we are all familiar with the way statistical claims can be sensationalised, particularly in the media. In the age of big data, as data science becomes established as a discipline, a basic grasp of statistical literacy is more important than ever. In The Art of Statistics, David Spiegelhalter guides the listener through the essential principles we need in order to derive knowledge from data. 

Artificial intelligence touches nearly every part of your day. While you may initially assume that technology such as smart speakers and digital assistants are the extent of it, AI has in fact rapidly become a general-purpose technology, reverberating across industries including transportation, healthcare, financial services, and many more. In our modern era, an understanding of AI and its possibilities for your organization is essential for growth and success. Artificial Intelligence Basics has arrived to equip you with a fundamental, timely grasp of AI and its impact. 

In industry after industry, data, analytics, and AI-driven processes are transforming the nature of work. While we often still treat AI as the domain of a specific skill, business function, or sector, we have entered a new era in which AI is challenging the very concept of the firm. AI-centric organizations exhibit a new operating architecture, redefining how they create, capture, share, and deliver value.  

Brought to you by Penguin. We think we know bullshit when we hear it, but do we? A spotter's guide to bullshit in the wild from two brilliantly contrarian scientists The world is awash in bullshit, and we're drowning in it. Politicians are unconstrained by facts. Science is conducted by press...

A FINANCIAL TIMES BOOK OF THE WEEK 'Illuminating' Eddie Jones 'Fantastic, a must-read for rugby fans' Ben Youngs 'Essential reading... reveals rugby's secrets' Financial Times 'Well written, insightful and thought-provoking' The Guardian 'Quite literally, the book on data in rugby' Irish Times...

Brought to you by Penguin. THE SUNDAY TIMES BESTSELLER AND A FINANCIAL TIMES, SUNDAY TIMES AND TELEGRAPH BOOK OF THE YEAR 2024 The insider account of the data revolution that has swept through the modern football world written by one of its key architects, Ian Graham. Between 2012 and 2023, Ian...

This audiobook is a summary of the advice I’ve given to software engineers over the years–and then some more. This audiobook follows the structure of a “typical” career path for a software engineer, from starting out as a fresh-faced software developer, through being a role model senior/lead, all the way to the staff/principle/distinguished level. It summarizes what I’ve learned as a developer and how I’ve approached coaching engineers at different stages of their careers.

What leads to political turbulence and social breakdown? How do elites maintain their dominant position? And why do ruling classes sometimes suddenly lose their grip on power? For decades, complexity scientist Peter Turchin has been studying world history like no one else. Assembling vast databases mined from 10,000 years of human activity, and then developing new models, he has transformed the way we learn from the past. End Times is the result: a ground-breaking account of how society works.

Data engineering has grown rapidly in the past decade, leaving many software engineers, data scientists, and analysts looking for a comprehensive view of this practice. With this practical book, you'll learn how to plan and build systems to serve the needs of your organization and customers by evaluating the best technologies available through the framework of the data engineering lifecycle.

Data fabric, data lakehouse, and data mesh have recently appeared as viable alternatives to the modern data warehouse. These new architectures have solid benefits, but they're also surrounded by a lot of hyperbole and confusion. This practical book provides a guided tour of these architectures to help data professionals understand the pros and cons of each.

FinOps brings financial accountability to the variable spend model of cloud. Used by the majority of global enterprises, this management practice has grown from a fringe activity to the de facto discipline managing cloud spend. In this book, authors J. R. Storment and Mike Fuller outline the process of building a culture of cloud FinOps by drawing on real-world successes and failures of large-scale cloud spenders. Complete with a road map to get you started, this revised second edition includes new chapters that cover forecasting, sustainability, and connectivity to other frameworks.

Data is at the center of many challenges in system design today. Difficult issues such as scalability, consistency, reliability, efficiency, and maintainability need to be resolved. In addition, there's an overwhelming variety of systems, including relational databases, NoSQL datastores, data...

In a world dazzled by digital promise, the profession of Data Science has acquired an almost mythical glow. Headlines celebrate it, industries chase it, and countless seekers imagine that mastery of this field will open a direct path to success. Yet behind this bright aura lies a more intricate reality—one shaped by discipline, ambiguity, intellectual rigor, and the quiet labour of confronting the unknown. This book invites the reader to step beyond the mirage and encounter the craft as it truly is.

You can be incredibly productive with Azure without mastering every feature, function, and service. Learn Azure in a Month of Lunches, Second Edition gets you up and running quickly, teaching you the most important concepts and tasks in 21 practical bite-sized lessons. As you explore the examples, exercises, and labs, you'll pick up valuable skills immediately and take your first steps to Azure mastery! This fully revised new edition covers core changes to the Azure UI, new Azure features, Azure containers, and the upgraded Azure Kubernetes Service.

This book is for people who are serious about how they can improve how their organizations run and how they can make their next large transformation project a success. It is for the process and architecture practitioners who run their programs for years and don’t get the visibility that they deserve. It is for the analysts who want to switch their practices to a data-driven approach (while not forgetting the human contributions in the analysis) and for whom the words “Digital Gemba” sound good.

Build intelligent LLM-powered applications with agentic workflows and tool-based agents. AI-powered applications are rapidly becoming the new normal. Personal productivity assistants, coding agents, smarter search, and automated reporting tools are popping up everywhere. The LangChain ecosystem, and standards like MCP are driving this new gold rush. This book helps you claim your spot.

In this comprehensive study guide, you will build a strong foundation in all topics covered on the certification exam, including the Databricks Lakehouse and its tools and benefits.

Becoming a Data Head is a complete guide for data science in the workplace: covering everything from the personalities you’ll work with to the math behind the algorithms. The authors have spent years in data trenches and sought to create a fun, approachable, and eminently bingeable book. Anyone can become a Data Head—an active participant in data science, statistics, and machine learning. Whether you're a business professional, engineer, executive, or aspiring data scientist, this book is for you.

Data analysis is a must-have skill that becomes more essential as the world becomes more data-driven. And one of the most effective ways to dive into data analysis is by learning a programming language. Python is a great place to start. This book explains everything you need to know to start using Python for data analysis.