Author: Data Science Central

Feed: Featured Blog Posts - Data Science Central. Author: HAN Lijun.   By JIANG Buxing, Data Scientist  Multidimensional analysis, commonly called OLAP, is an interactively data analysis process that performs operations, including rotation, slice and dice, drilldown etc., on a data cube. The structure of its back-end computation is simple, as shown by the following SQL: SELECT D,..., SUM(M), ... FROM C WHERE D'=d' AND ... GROUP BY D,... The statement aggregates some measures by some dimensions. C is a data cube, D,… represents dimensions to be selected, and M,… represents measures to be aggregated. Except for SUM, we can ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Vincent Granville. This article is by Jitesh Shah, a data & stats jockey in perpetual beta, located in Fremont, California. This article includes the data set and Python code. Wouldn’t it be nice if defects and product failures can be predicted in advance. We’ve got the data on attributes and design features and manufacturing processes that come together and creates that product and we have defect and failure rate data so all we got to do is connect the two and use that to predict which set of features and attributes and processes in ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Sandipan Dey. This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Summary In this report, the spread of the pandemic influenza A (H1N1) that had an outbreak in Kolkata, West Bengal, India, 2010 is going to be simulated. The basic epidemic SIR model will be used, it describes three populations: a susceptible population, an infected population, and a recovered population and assumes the total population (sum of these 3 populations) as fixed over the period of study. There are two parameters for this model: namely the attack rate (β) per infected person per day through contacts and the recovery rate (α). Initially there will be a ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Amelia Matteson. This article was written by Michael Rundell. A Curated List of Data Science Interview Questions Preparing for an interview is not easy – naturally there is a large amount of uncertainty regarding the data science interview questions you will be asked. No matter how much work experience or technical skill you have, an interviewer can throw you off with a set of questions that you didn’t expect. For a data science interview, an interviewer will ask questions spanning a wide range of topics, requiring strong technical knowledge and communication ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Pablo Bernabeu. Dashboards for data visualization, such as Tableau or R Shiny, enable an interactive exploration of data in the form of plots or tables, through a programming-free interface with drop-down lists and checkboxes. The apps can be useful for both the data analyst and the public. Visualization apps may be privately consulted as well as published online. There are two main platforms: R Shiny and Tableau. Shiny has a free starter license with limited use, where free apps can handle a certain amount of data, and up to five apps ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Venkatesan M. Amazon Web Services (AWS) is a dynamic, growing business unit within Amazon.com.Since early 2006, Amazon Web Services has provided companies of all sizes with an infrastructure platform in the cloud .Using AWS, companies can requisition compute power, storage, and other services– gaining access to a global computing infrastructure .   As the use of cloud computing increases day by day and many companies from startup to large corporate moving on to AWS, jobs with AWS skills also emerge. The question is are you on the right AWS career path?  While the boom of cloud computing ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Sheetal Sharma. There is a huge hype of Big Data and its features, most of them have been summed up in 9 different Vs of Big data like Volume, Velocity, Variety, Veracity, Validity, Volatility, Value, Variability, Viscosity. In a recently published white paper by credit reference agency Experian, a proposal has been given to add another “V” to the Big Data features Vulnerability. With the increasing size of people personal data, they have started feeling that it is being used to pry into their behavior to sell them things by different ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Vincent Granville. Here are some recommended boos for data science practitioners, covering machine learning, deep learning, business intelligence, forecasting, text analytics and much more. Book Repository for Data Scientists New Book: Analytics - How to Win with Intelligence  Python Data Science Handbook  Mastering Machine Learning with Python in Six Steps  Book review: The Mathematical Corporation  Machine Learning with R - Second Edition  Data Science for the Layman  Java Deep Learning Essentials  80+ Free Data Science Books  Data for Business Performance  10 Free Machine Learning books  27 free data mining books  Evaluating ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Patrick Baranowsky. Strategic application of data and analysis often involve driving decisions.  According to Merriam-Webster, a ‘decision’ can be defined as a determination arrived at after consideration.  Whether it be political debates, litigation, business cases, or household endeavors, people arrive at an incredible variety of determinations, but often with questionable consideration.  While little consideration may be warranted for example to decide whether to buy a blue or green dish soap, significant consideration should drive other determinations, such as for investments and legal judgments.  Such consideration should include logical and distinguishing analytics, ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Shreya Gupta. 1. Objective Through this blog you will know about the Big data  applications and Big data uses in retail sector with examples along with use of RFID in retail. You will learn concepts related to Big data in retail industry like retail asset management, production tracking in retails industry, inventory control, Shipment, Regulatory Compliance, and Service and Warranty Authorizations and many other retail Big data use cases with examples. 2. Use of Big Data in Retail Industry With the growth in retail industry with millions of transactions spread across multiple ... Read More