検索キーワード： データサイエンス

Veteran data and analytics professional delivers a practical and hands-on discussion on how to accelerate business results using high-quality data.

This book bridges the gap between strictly technical books about the blockchain and the research-based books primarily concerned with practical applications, discussions of its expected economic effect, and future visions. It will be your guide through the unknown and complicated world of cryptocurrency and blockchain technology.

This book consists of 6 titles, namely: Assembly Language: The Ultimate Guide to Programming and Virtual Machines. Computer Science: The Complete Guide to Principles and Informatics. Cyber Security: Beginners’ Guide to Hacking, Phishing, Social Engineering, and Malware. Databases: System Concepts, Designs, Management, and Implementation. Operating Systems: Concepts to Save Money, Time, and Frustration. Website Development: Web Design Skills for Beginners

Everybody has heard of it - but who can explain it? In simple terms? This audiobook! After his latest best seller Cryptocurrencies Simply Explained, Dr. Julian Hosp now explains blockchain in a simple way - the next revolution. And it is far more than just Bitcoin, Ethereum, ICOs and Co. You will learn about dangers and weaknesses as well as chances of the blockchain technology. It is not a question if it will come, but when. Be prepared and learn today about the world of tomorrow.

R in Action, Second Edition teaches you how to use the R language by presenting examples relevant to scientific, technical, and business developers. Focusing on practical solutions, the book offers a crash course in statistics, including elegant methods for dealing with messy and incomplete data. You'll also master R's extensive graphical capabilities for exploring and presenting data visually. And this expanded second edition includes new chapters on forecasting, data mining, and dynamic report writing.

Whether you are at a beginner or intermediate level, this book is crafted just for you. Learn Python fundamentals. This is your beginner's step-by-step guide to one of the most essential, renowned, and practical programming languages in the 21st century. Python is a general purpose program used by many start-ups. Its design emphasizes code readability.

Until very recently, if you were to ask most doctors, they would tell you there were only two kinds of medicine: the quack kind, and the evidence-based kind. The former is baseless, and the latter based on the best information human effort could buy. Well, Eric Topol isn't most doctors, and he suggests you entertain the notion of a third kind of medicine, one that will make the evidence-based state-of-the-art stuff look scarcely better than an alchemist trying to animate a homunculus in a jar.

List the hottest buzzwords in business today and "analytics" is bound to come out near the top. But to most people, analytics implies complex tools and technical experts manipulating massive amounts and varieties of information (i.e.,"Big Data"). But complex Big Data analytics isn't the only game in town. And many people don't realize that a business doesn't need data scientists and complex tools to derive useful information and valuable benefits from any amount of raw data.

The ability to effectively communicate with data is no longer a luxury in today’s economy; it is a necessity. Transforming data into visual communication is only one part of the picture. It is equally important to engage your audience with a narrative—to tell a story with the numbers. Effective Data Storytelling will teach you the essential skills necessary to communicate your insights through persuasive and memorable data stories.

Data Leadership for Everyone is a game-changing book for anyone who believes in the power of data and is ready to create revolutionary change in their organization. Whether you're a C-suite executive, a manager, or an individual contributor, this book will propel your career by unlocking the mystery of how raw data transforms into real outcomes.

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.

Slow systems are frustrating. They waste time and money. But making consistently great decisions about performance can be easy, if you understand what's going on. This book explains in a clear and thoughtful voice why systems perform the way they do. It's for anybody who's curious about how computer programs and other processes use their time and about what you can do to improve them. Through a mix of personal vignettes and technical use cases, Cary Millsap reviews the process of improving performance and provides best practices for optimizing systems efficiently.

Millions of data enthusiasts from around the world compete on Kaggle, the most famous data science competition platform of them all. Participating in Kaggle competitions is a surefire way to improve your data analysis skills, network with an amazing community of data scientists, and gain valuable experience to help grow your career. The first audiobook of its kind, The Kaggle Book assembles in one place the techniques and skills you'll need for success in competitions, data science projects, and beyond.

By the end of on average day in the early 21st century, human beings searching the Internet will amass eight trillion gigabytes of data. This staggering amount of information - unprecedented in history - can tell us a great deal about who we are - the fears, desires, and behaviors that drive us, and the conscious and unconscious decisions we make. From the profound to the mundane, we can gain astonishing knowledge about the human psyche that less than 20 years ago seemed unfathomable.

Imagine a world where your data isn’t controlled by faceless corporations. A world where the internet isn’t a walled garden, but a boundless frontier of freedom, security, and opportunity. Welcome to Decentralizing the Future: The Story of Flux and the Rise of Web3. In this riveting journey, we unravel the story of the internet’s next great leap from the centralized grip of Web2, where a handful of tech giants hold the keys, to the decentralized promise of Web3. At the heart of this revolution is Flux, a trailblazer building the backbone of a new digital world.

Curious about AI but unsure where to start? AI for Beginners Made Simple breaks down complex concepts into clear, practical insights—no tech background required! Discover how AI can enhance your career, automate tasks, and open new opportunities with easy-to-follow explanations, real-world applications, and hands-on projects. Learn AI basics, navigate ethical concerns, and access free resources—all without the jargon overload.

Data projects are an intrinsic part of an organization's technical ecosystem, but data engineers in many companies continue to work on problems that others have already solved. This hands-on guide shows you how to provide valuable data by focusing on various aspects of data engineering, including data ingestion, data quality, idempotency, and more.

Structured query language, or SQL (pronounced "sequel" by many), is the most widely used programming language in database management and is the standard language for relational database management systems (RDBMS). SQL programming allows users to return, analyze, create, manage, and delete data within a database - all within a few commands.

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.

Data science happens in code. The ability to write reproducible, robust, scaleable code is key to a data science project's success—and is absolutely essential for those working with production code. This practical book bridges the gap between data science and software engineering, and clearly explains how to apply the best practices from software engineering to data science.