Showing titles in Data Science

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.

Big Data teaches you to build big data systems using an architecture designed specifically to capture and analyze web-scale data. This book presents the Lambda Architecture, a scalable, easy-to-understand approach that can be built and run by a small team. You'll explore the theory of big data systems and how to implement them in practice. In addition to discovering a general framework for processing big data, you'll learn specific technologies like Hadoop, Storm, and NoSQL databases.

Blockchain technology presents an alternative to corrupt and centralized institutions, as well as costly and inefficient middlemen. Whether you’re looking to use it to improve your business, invest in cryptocurrencies, or just learn for curiosity’s sake, this book will help answer your questions and show you why there is so much buzz about blockchain.

Drawing on years of work interpreting and explaining data about almost anything, renowned data journalist Kiko Llaneras offers practical tools and shortcuts to help you understand the numbers and make better decisions using a quantitative lens. Through a series of compelling examples, he reveals some of the surprising insights that a data-driven perspective can offer.

There are two remarkable phenomena that are unfolding almost simultaneously. The first is the emergence of a data-first world, where data has become a central driving force, shaping industries and fueling innovation. The second is the dawn of the AI age, propelled by the advent of Generative AI...

As any Leeds United fan will tell you, following the Whites is certainly never boring. Almost as famous for their periods of chaos as for their moments of glory, over the years supporters have been left exhilarated and exasperated in equal measure - whilst remaining one of the most passionate...

'Shivam Shankar Singh and Anand Venkatanarayanan's stellar examination of how modern conjurers apply the art of perception management to shape reality uses wonderful Indian epics and pop culture stories to convey complex information-warfare concepts like reflexive control, cybercriminal...

The use of analytics in sport is now well embedded. Marginal gains, the bedrock upon which the cycling coach Dave Brailsford built his greatest successes, are cornerstones of most sports nowadays. But, until recently, that did not apply to the biggest sport in the world. Not in soccer. It was as though this simplest of sports is too complicated for statistics. Or that only one statistic counts, the number of times the ball hits the back of the net. "The only statistic that counts", there’s an often used and annoying stock term.

A guide of python cyber.

"Big Data" is on the covers of Science, Nature, The Economist, and Wired magazines, on the front pages of the Wall Street Journal and The New York Times. But despite the media hyperbole, as Christine Borgman points out in this examination of data and scholarly research, having the right data is usually better than having more data; little data can be just as valuable as big data. Borgman, an often-cited authority on scholarly communication, argues that data have no value or meaning in isolation; they exist within a knowledge infrastructure.

This book is a scientific expedition to research and explore the enterprise-grade big data appliances with blended OLTP and OLAP capabilities. Enterprise database systems with the aid of big data analytics create an intelligent ecosystem by taming and wrangling the data coming from extreme-disparate sources of structured and unstructured channels with massive parallelization techniques to discover, visualize, predict, and action the patterns and trends of mashups of big data.

Real-World Machine Learning will teach you the concepts and techniques you need to be a successful machine learning practitioner without overdosing you on abstract theory and complex mathematics. By working through immediately relevant examples in Python, you'll build skills in data acquisition and modeling, classification, and regression. You'll also explore the most important tasks like model validation, optimization, scalability, and real-time streaming. When you're done, you'll be ready to successfully build, deploy, and maintain your own powerful ML systems.

Knowing how to craft SQL queries and navigate your way around a database is an essential skill if are a Database Administrator, System Administrator, or Programmer. This book guides you step-by-step by teaching you how to create databases, populate those databases with data, extract just the data you need, and much more.

Welcome to "Predictive Power: Navigating the Landscape of AI Systems and Decision-Making." In this book, we embark on a journey into the fascinating world of artificial intelligence (AI) systems and their profound impact on decision-making processes across various domains. From business and healthcare to finance and beyond, AI technologies are revolutionizing and transforming how we analyze data, predict outcomes, and make informed choices.

Data and analytics are essential for any business, giving insight into what's working, what can be improved, and what else needs to be done. SAS software helps you make sure you're doing data right, with a host of data management, reporting, and analysis tools. SAS for Dummies teaches you the essentials, helping you navigate this statistical software and turn information into value.

In einer Welt, in der alles miteinander kommuniziert, entsteht eine neue Art von Intelligenz: vernetzt, effizient und nachhaltig. Dieses Buch zeigt, wie IoT, LoRaWAN und smarte Netzwerke zusammenwirken, um Prozesse zu optimieren, Energie zu sparen und neue digitale Lösungen zu schaffen. Du erfährst Schritt für Schritt, welche Einsatzmöglichkeiten moderne IoT-Systeme bieten.

Radically improve the quality of your data visualizations by employing core principles of color, typography, chart types, data storytelling, and more. Everyday Data Visualization is a field guide for design techniques that will improve the charts, reports, and data dashboards you build every day. Everything you learn is tool-agnostic, with universal principles you can apply to any data stack.

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...

Celebrated data-driven growth leader Lillian Pierson delivers a masterclass in developing custom strategies to harness the full potential of data and AI within your organization. This book offers a clear, actionable roadmap for leveraging your company's data and technology assets to drive significant, reliable growth.