Big Data & Business Intelligence

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Learning SQL Server 2016 Reporting Services [Video]
$ 89.25
Your guide to creating intuitive, cross-platform reports with SQL Server 2016 Reporting Services
Learning Qlikview 12 [Video]
$ 85.00
Build powerful BI solutions with the finest BI tool on the market
Data Science with Spark [Video]
$ 39.00
Get started with Spark for data science using this unique video tutorial
R Machine Learning solutions [Video]
$ 85.00
Build powerful predictive models in R
Odoo 10 Development Essentials
$ 35.99
Fast-track your development skills to build powerful Odoo 10 business applications
Tableau 10 Business Intelligence Cookbook
$ 39.99
Create powerful, effective visualizations to help analyze your data with Tableau 10 by your side
Learning Jupyter
$ 39.99
Learn how to write code, mathematics, graphics, and output, all in a single document, as well as in a web browser using Project Jupyter
MDX with Microsoft SQL Server 2016 Analysis Services Cookbook - Third Edition
$ 43.99
Over 70 practical recipes to analyze multi-dimensional data in SQL Server 2016 Analysis Services cubes
OCP 12c Upgrade 1Z0-060 Exam Guide
$ 47.99
Your ultimate guide to passing the OCP 12c Upgrade 1Z0-060 Exam
Introduction to QGIS Python Programming [Video]
$ 72.25
Learn how to analyze and display geospatial information using QGIS and Python
SQL Server 2016 Reporting Services Cookbook
$ 43.99
Create interactive cross-platform reports and dashboards using SQL Server 2016 Reporting Services
Bayesian Analysis with Python
$ 39.99
Unleash the power and flexibility of the Bayesian framework
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Latest from the Blog

Keep ahead of the curve with the latest expert insight, detailed technical analysis, and original research.

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The R Statistical Package Interfacing with Python

In this post, we talk about the package rpy2, which is used to call R inside of python

Vector Representation of Words

There are various ways to express a textual document as a vector depending on the problem and the assumptions of the model. In traditional Vector Space Models (VSMs), a word is represented as a vector of dimension equal to the size of vocuabulary with each word in the vocabulary corresponds to an entry in the vector.