General

Learn how to use Power BI to deliver the insights needed to help your enterprise survive and thrive Purchase of the print or Kindle book includes a free eBook in PDF format. Key Features Learn simple through to advanced Power BI features in a...

Utilize a new layers-based development model for embedded systems using Agile techniques for software architecture and management. Firmware is comprised of both hardware and software, but the applicability of Agile in embedded systems development is new...

Computation, itself a form of calculation, incorporates steps that include arithmetical and non-arithmetical (logical) steps following a specific set of rules (an algorithm). This uniquely accessible textbook introduces students using a very distinctive...

Now that people are aware that data can make the difference in an election or a business model, data science as an occupation is gaining ground. But how can you get started working in a wide-ranging, interdisciplinary field that's so clouded in hype?...

The second edition of Consumer Behaviour and Analytics provides a consumer behaviour textbook for the new marketing reality. In a world of Big Data, machine learning and artificial intelligence, this key text reviews the issues, research and concepts...

Data is getting bigger, arriving faster, and coming in varied formats-and it all needs to be processed at scale for analytics or machine learning. How can you process such varied data workloads efficiently? Enter Apache Spark. Updated to emphasize...

Learn the basics of Data Science through an easy to understand conceptual framework and immediately practice using RapidMiner platform. Whether you are brand new to data science or working on your tenth project, this book will show you how to analyze...

Combing the web is simple, but how do you search for data at work? It's difficult and time-consuming, and can sometimes seem impossible. This book introduces a practical solution: the data catalog. Data analysts, data scientists, and data engineers will...

Work through practical recipes to learn how to automate complex machine learning and deep learning problems using Python Key Features * Get up and running with AI (artificial intelligence) in no time using hands-on problem-solving recipes * Explore...

"My absolute favorite for this kind of interview preparation is Steven Skiena's The Algorithm Design Manual. More than any other book it helped me understand just how astonishingly commonplace ... graph problems are -- they should be part of every...

Systems Thinkers presents a biographical history of the field of systems thinking, by examining the life and work of thirty of its major thinkers. It discusses each thinker's key contributions, the way this contribution was expressed in practice and the...

Tools from macroeconomics and finance to incorporate the central role that data plays in the economyThe most valuable firms in the global economy are valued largely for their data. Amazon, Apple, Google, and others have proven the competitive advantage...

Social Learning Systems and Communities of Practice is a collection of classical and contemporary writing associated with learning and systemic change in contexts ranging from cities, to rural development to education to nursing to water management to...

Get going with tidymodels, a collection of R packages for modeling and machine learning. Whether you're just starting out or have years of experience with modeling, this practical introduction shows data analysts, business analysts, and data scientists...

An engaging introduction to data science that emphasizes critical thinking over statistical techniquesAn introduction to data science or statistics shouldn't involve proving complex theorems or memorizing obscure terms and formulas, but that is exactly...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9780262547932Author Cristina AlaimoFormat PaperbackPage Count 240Imprint MIT PressPublisher MIT Press Ltd

"My absolute favorite for this kind of interview preparation is Steven Skiena's The Algorithm Design Manual. More than any other book it helped me understand just how astonishingly commonplace ... graph problems are -- they should be part of every...

There's growing interest in learning how to analyze streaming data in large-scale systems such as web traffic, financial transactions, machine logs, industrial sensors, and many others. But analyzing data streams at scale has been difficult to do...

How to build and maintain strong data organizations-the Dummies way Data Governance For Dummies offers an accessible first step for decision makers into understanding how data governance works and how to apply it to an organization in a way that improves...

While Excel remains ubiquitous in the business world, recent Microsoft feedback forums are full of requests to include Python as an Excel scripting language. In fact, it's the top feature requested. What makes this combination so compelling? In this...

The time has now come when graph theory should be part of the education of every serious student of mathematics and computer science, both for its own sake and to enhance the appreciation of mathematics as a whole. This book is an in-depth account of...

What do you need to become a data-driven organization? Far more than having big data or a crack team of unicorn data scientists, it requires establishing an effective, deeply-ingrained data culture. This practical book shows you how true data-drivenness...

Ingest, transform, manipulate, and visualize your data beyond Power BI's capabilities. Purchase of the print or Kindle book includes a free eBook in PDF format. Key Features Discover best practices for using Python and R in Power BI by...

Build a continuously learning and adapting organization that can extract increasing levels of business, customer and operational value from the amalgamation of data and advanced analytics such as AI and Machine Learning Key Features Master the Big...

Build powerful data analytics applications with this business intelligence tool and overcome all your business challengesKey FeaturesMaster time-saving techniques and make your QlikView development more efficientPerform geographical analysis and...

Build real-world time series forecasting systems which scale to millions of time series by applying modern machine learning and deep learning concepts Key Features Explore industry-tested machine learning techniques used to forecast millions of...

Leading tech companies such as Netflix, Amazon and Uber use data science and machine learning at scale in their core business processes, whereas most traditional companies struggle to expand their machine learning projects beyond a small pilot scope...

This book provides a comprehensive treatment of the rapidly changing world of Web-based business technologies and their often-disruptive innovations. The history of the Web is a short one. Indeed many college graduates today were not even born when the...

Since long before computers were even thought of, data has been collected and organized by diverse cultures across the world. Once access to the Internet became a reality for large swathes of the world's population, the amount of data generated each day...

Learn the 5% of Python programming knowledge which exponentially accelerates your learning curve for the remaining 95%.Alleviate the overwhelm of "too much to learn, not enough time". This book cuts through the noise to focus on the "accelerators" that...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9781607857464Author Stanley ChanFormat HardbackPage Count 704Imprint Michigan Publishing ServicesPublisher Michigan Publishing ServicesWeight(grams)...

Effective visualization is the best way to communicate information from the increasingly large and complex datasets in the natural and social sciences. But with the increasing power of visualization software today, scientists, engineers, and business...

Doing Science With Python introduces readers to the most popular coding tools for scientific research, such as Anaconda, Spyder, Jupyter Notebooks, and JupyterLab, as well as dozens of important Python libraries for working with data, including NumPy,...

Fast Python for Data Science is a hands-on guide to writing Python code that can process more data, faster, and with less resources. It takes a holistic approach to Python performance, showing you how your code, libraries, and computing architecture...

Learn how to use, deploy, and maintain Apache Spark with this comprehensive guide, written by the creators of the open-source cluster-computing framework. With an emphasis on improvements and new features in Spark 2.0, authors Bill Chambers and Matei...

Machine Learning, a vital and core area of artificial intelligence (AI), is propelling the AI field ever further and making it one of the most compelling areas of computer science research. This textbook offers a comprehensive and unbiased introduction...

This book is for executives, practitioners, and project managers who are tasked with the movement of data from old systems to a new repository. It is designed as a practical guide and uses a series of steps developed in real-life situations that will get...

Use this guide book in its fully updated second edition to study for the ITIL 4 Foundation certification exam. Know the latest ITIL framework and DevOps concepts.The book will take you through the new ITIL framework and nuances of the DevOps methodology...

This book is about the harmonious synthesis of functional programming and numerical computation. It shows how the expressiveness of OCaml allows for fast and safe development of data science applications. Step by step, the authors build up to use cases...

Digital transformation is a vital practice for organizations trying to keep up with competitors, but with new digital approaches constantly promising to revolutionize the workplace it can feel impossible to keep up. Cut through the hype with this...