Showing titles in Data Science

When "metadata" became breaking news, appearing in stories about surveillance by the National Security Agency, many members of the public encountered this once-obscure term from information science for the first time. Should people be reassured that the NSA was "only" collecting metadata about phone calls - information about the caller, the recipient, the time, the duration, the location - and not recordings of the conversations themselves? Or does phone call metadata reveal more than it seems?

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.

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.

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.

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

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.

ChatGPT for Beginners is a practical, step-by-step guide designed for entrepreneurs and side hustlers who want to use artificial intelligence without feeling overwhelmed. If you’re curious about ChatGPT but unsure how to apply it to real business tasks, this beginner-friendly guide breaks everything down in clear, simple language. You’ll learn how to use ChatGPT for productivity, content creation, marketing, planning, and everyday business support—no technical background required.

“One of my favorite books of the year. It completely reshaped how I think about information and how and why I take notes.” —Daniel Pink, bestselling author of Drive A revolutionary approach to enhancing productivity, creating flow, and vastly increasing your ability to capture, remember...

Graph-Powered Machine Learning teaches to use graph-based algorithms and data organization strategies to develop superior machine learning applications. You’ll dive into the role of graphs in machine learning and big data platforms, and take an in-depth look at data source modeling, algorithm design, recommendations, and fraud detection. Explore end-to-end projects that illustrate architectures and help you optimize with best design practices.

Law today is incomplete, inaccessible, unclear, underdeveloped, and often perplexing to those whom it affects. In The Legal Singularity, Abdi Aidid and Benjamin Alarie argue that the proliferation of artificial intelligence-enabled technology–and specifically the advent of legal prediction–is on the verge of radically reconfiguring the law, our institutions, and our society for the better.

In Fusion Strategy, world-renowned innovation guru Vijay Govindarajan and digital strategy expert Venkat Venkataraman offer a first-of-its-kind playbook that will help industrial companies combine what they do best-create physical products-with what digitals do best-use algorithms and AI to parse expansive, interconnected datasets-to make strategic connections that would otherwise be impossible.

A team of dedicated tech executives delivers a business-focused approach based on a deep and engaging exploration of the models and data used in causal AI. The book’s discussions include both accessible and understandable technical detail and business context and concepts that frame causal AI in familiar business settings.

If you need to learn Spring, look no further than this widely beloved and comprehensive guide! Fully revised for Spring 5.3, and packed with interesting real-world examples to get your hands dirty with Spring. Over the years, Spring in Action has helped tens of thousands of developers get a major productivity boost from Spring. This new edition of the classic best seller covers all of the new features of Spring 5.3 and Spring Boot 2.4 along with examples of reactive programming, Spring Security for REST Services, and bringing reactivity to your databases.

This audiobook is narrated by an AI Voice. As organizations generate more data than ever before, traditional centralized data platforms often struggle to keep up with growing complexity, scalability challenges, and slow decision-making. Modern businesses need a smarter, faster, and more flexible...

10,000 hours. That’s what it takes to be an expert at anything. Art. Sport. Music. And Data. You might not yet have clocked your quota of designing databases, business intelligence applications, reports, or analytics.

Are you aspiring to become an AWS Certified Developer? Are you looking for a comprehensive resource to prepare for the AWS Certified Developer exam? Look no further! This book is your ultimate guide to acing the AWS Certified Developer certification by providing you with a robust set of practice test questions and detailed answers to help you succeed.

Take advantage of today's sky-high demand for data engineers. With this in-depth book, current and aspiring engineers will learn powerful real-world best practices for managing data big and small. Contributors from notable companies including Twitter, Google, Stitch Fix, Microsoft, Capital One, and LinkedIn share their experiences and lessons learned for overcoming a variety of specific and often nagging challenges. Edited by Tobias Macey, this book presents ninety-seven concise and useful tips for cleaning, prepping, wrangling, storing, processing, and ingesting data.

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.

Today's business environment brings with it an onslaught of data. Now more than ever, managers must know how to tease insight from data—to understand where the numbers come from, make sense of them, and use them to inform tough decisions. How do you get started? Whether you're working with data experts or running your own tests, you'll find answers in the HBR Guide to Data Analytics Basics for Managers. This book describes three key steps in the data analysis process, so you can get the information you need, study the data, and communicate your findings to others.

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.