Learn to create an effective business strategy using Microsoft’s BI stack
Microsoft Business Intelligence tools are among the most widely used applications for gathering, providing access to, and analyzing data to enable the enterprise to make sound business decisions. The tools include SharePoint Server, the Office Suite, PerformancePoint Server, and SQL Server, among others.
Azure ML, Microsoft’s Azure Machine Learning cloud platform, provides an easy-to-use and powerful set of cloud-based data transformation and machine-learning tools. With this O’Reilly report, you’ll learn the basics of manipulating data and constructing and evaluating models in Azure ML, illustrated by a complete data science example.
You don’t need a technical background to build powerful databases with FileMaker Pro 14. This crystal-clear, objective guide shows you how to create a database that lets you do almost anything with your data so you can quickly achieve your goals. Whether you’re creating catalogs, managing inventory and billing, or planning a wedding, you’ll learn how to customize your database to run on a PC, Mac, web browser, or iOS device.
This book is a practical guide that explains the classification algorithms provided in Apache Mahout with the help of actual examples. Starting with the introduction of classification and model evaluation techniques, we will explore Apache Mahout and learn why it is a good choice for classification.
New technologies have enabled us to collect massive amounts of data in many fields. However, our pace of discovering useful information and knowledge from these data falls far behind our pace of collecting the data. Data Mining: Theories, Algorithms, and Examples introduces and explains a comprehensive set of data mining algorithms from various data mining fields. The book reviews theoretical rationales and procedural details of data mining algorithms, including those commonly found in the literature and those presenting considerable difficulty, using small data examples to explain and walk through the algorithms.