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Microsoft Business Intelligence For Dummies

Microsoft Business Intelligence For Dummies

by Ken Withee
432 Pages · 2010 · 9.03 MB · 1,007 Downloads · New!
" Happiness doesn't result from what we get, but from what we give. ” ― Ben Carson
Data Science in the Cloud with Microsoft Azure Machine Learning and R
by Stephen Elston
65 Pages · 2015 · 1.87 MB · 1,038 Downloads · New!
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.
FileMaker Pro 14: The Missing Manual
by Stuart Gripman
972 Pages · 2015 · 36.23 MB · 3,834 Downloads · New!
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.
Teach Yourself VISUALLY Access 2013
by Paul McFedries
339 Pages · 2013 · 33.83 MB · 1,753 Downloads · New!
The easy, visual way to learn this popular database program
Learning Apache Mahout Classification
by Ashish Gupta
130 Pages · 2015 · 2.43 MB · 1,748 Downloads · New!
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.
Access 2013 All-in-One For Dummies
by Alison Barrows
792 Pages · 2013 · 26,89 MB · 1,098 Downloads · New!
Get started with the new Access 2013 with this impressive all-in-one reference!
Data Mining: Theories, Algorithms, and Examples
by Nong Ye
349 Pages · 2013 · 6.55 MB · 4,404 Downloads · New!
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.