Showing titles in Data Science

Docker in Action teaches listeners how to create, deploy, and manage applications hosted in Docker containers. After starting with a clear explanation of the Docker model, you will learn how to package applications in containers, including techniques for testing and distributing applications. You will also learn how to run programs securely and how to manage shared resources. Using carefully designed examples, the book teaches you how to orchestrate containers and applications from installation to removal.

Time Series Forecasting in Python teaches you to build powerful predictive models from time-based data. Every model you create is relevant, useful, and easy to implement with Python. You’ll explore interesting real-world datasets like Google’s daily stock price and economic data for the USA, quickly progressing from the basics to developing large-scale models that use deep learning tools like TensorFlow.

In this explosive memoir, a political consultant and technology whistleblower reveals the disturbing truth about the multi-billion-dollar data industry, revealing to the public how companies are getting richer using our personal information and exposing how Cambridge Analytica exploited weaknesses in privacy laws to help elect Donald Trump - and how this could easily happen again in the 2020 presidential election.

Scott Hartley first heard the terms fuzzy and techie while studying political science at Stanford University. If you majored in the humanities or social sciences, you were a fuzzy. If you majored in the computer sciences, you were a techie. This informal division has quietly found its way into a default assumption that has misled the business world for decades: that it's the techies who drive innovation.

This friendly guide teaches you how to apply common algorithms to the practical problems you face every day as a programmer. You'll start with sorting and searching and, as you build up your skills in thinking algorithmically, you'll tackle more complex concerns such as data compression and artificial intelligence. This accesible introduction is suitable for self-taught programmers, engineers, or anyone who wants to brush up on algorithms. Each carefully presented example includes helpful diagrams and fully annotated code samples in Python.

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.

The data lakehouse is the next generation of the data warehouse and data lake, designed to meet today’s complex and ever-changing modern information systems. This book shows you how to construct your data lakehouse as the foundation for your artificial intelligence (AI), machine learning (ML), and data mesh initiatives. Know the pitfalls and techniques for maximizing business value of your data lakehouse. In addition, be able to explain the core characteristics and critical success factors of a data lakehouse. By reviewing entry errors, key incompatibility, and ensuring good documentation...

When it comes to choosing, using, and maintaining a database, understanding its internals is essential. But with so many distributed databases and tools available today, it's often difficult to understand what each one offers. With this practical guide, Alex Petrov guides developers through the concepts behind modern database and storage engine internals.

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

Today, number crunching affects your life in ways you might never imagine. In this lively and groundbreaking new audiobook, economist Ian Ayres shows how today's best and brightest organizations are analyzing massive databases at lightening speed to provide greater insights into human behavior. They are the Super Crunchers.

Focusing on the business and financial value of big data analytics, respected technology journalist Frank J. Ohlhorst shares his insights on the newly emerging field of big data analytics in Big Data Analytics. This breakthrough book demonstrates the importance of analytics, defines the processes, highlights the tangible and intangible values, and discusses how you can turn a business liability into actionable material that can be used to redefine markets, improve profits, and identify new business opportunities.

Improve your organization’s odds of succeeding with artificial intelligence. Managers struggle to determine whether they have the right people, knowledge, data, and tools to compete in a new business landscape―a landscape revolutionized by AI. Although most leaders ‘hope’ that they have the ‘right stuff’, hope is not a strategy. Organizations must critically assess where they are currently and what gaps they must fill to be competitive in this new environment. Through questionnaires and assessments covering eight critical dimensions, this book will help you build the foundation ...

The discipline of infonomics takes you beyond thinking and talking about information as an asset to actually valuing and treating it as one. Infonomics provides the foundation and methods for quantifying information asset value and tactics for using information as your competitive edge to drive growth.

Every company today relies on data, yet many leadership teams struggle to fully leverage data as an asset while avoiding ethics scandals that erode consumer trust. This indispensable guide provides executives and board members an actionable playbook to transform their organization into an ethical data leader poised for innovation and growth.

We are living in the age of information and there’s no denying it—those who are best at organizing, understanding, and then using data to their advantage will be the ones on top. The skills themselves are simple and easy to learn and will give you a tremendous advantage in the highly competitive marketplace of today’s workforce. The only thing left is for you to give a little commitment and launch yourself into a whole new reality of success.

Whether you're a complete novice or a seasoned enthusiast, this comprehensive guide is your ticket to mastering the art of ham radio operation. Go into the rich history and evolution of ham radio, from its early beginnings during World War I to its pivotal role in disaster communications and beyond. Explore the fascinating world of electromagnetic spectrum, transmission modes, and the essential components of a ham radio station.

Algorithms and Data Structures for Massive Datasets reveals a toolbox of new methods that are perfect for handling modern big data applications. You’ll explore the novel data structures and algorithms that underpin Google, Facebook, and other enterprise applications that work with truly massive amounts of data.

Computer science is a field that deals with the study of computers and computational systems. It encompasses both the theoretical and practical aspects of computing, including algorithms, data structures, programming languages, software engineering, and more. It's about understanding how computers work, how they can solve problems, and how they interact with humans and other systems.

Welcome to "NewSQL Essentials: Scaling Relational Databases for the Cloud Era." This book is a comprehensive guide that aims to equip you with the knowledge and skills to harness the power of NewSQL databases in the context of the rapidly evolving cloud landscape. In recent years, we have witnessed an exponential growth in data volumes and the increasing demand for scalable, high-performance databases. Traditional relational databases, while reliable and feature-rich, face challenges in meeting the demands of modern applications that require massive scalability, real-time processing, and ...

Master the concepts and strategies underlying success and progress in data science. From the author of the bestsellers, Data Scientist and Julia for Data Science, this book covers four foundational areas of data science. The first area is the data science pipeline including methodologies and the data scientist's toolbox. The second are essential practices needed in understanding the data including questions and hypotheses. The third are pitfalls to avoid in the data science process. The fourth is an awareness of future trends and how modern technologies like Artificial Intelligence (AI) fit...