So far in this series on Artificial Intelligence Artificial Intelligence: Monster or Mentor? and AI for Summarization – Enabling Human-Consumable Information, we looked at several key ways in which AI advances can improve human productivity in…

By JIANG Buxing, Data Scientist 

As big data concept gains momentum, unstructured data analytics technology is becoming hot.  It is said that 80% of all data in an enterprise is unstructured, which is roughly true when it is measured by the space, considering the large size of the audio and video data. With huge amounts of data at hand, some technique is required to analyze them.

But make sure you are not misled by the universal unstructured data analytics…

Monday newsletter published by Data Science Central. Previous editions can be found here.  The contribution flagged with a + is our selection for the picture of the week.

Announcement

• Data Scientist - Sainsbury's - Predicting customer behaviour, scheduling driver…

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…

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…

Want to learn machine learning? Looking for data science tutorials and guides to help you master your data and produce actionable, game-changing insights?

Look no further than this list of machine learning eBooks from the Packt team....

1. …

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…

Amazon Web Services (AWS) is a dynamic, growing business unit within Amazon.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…

In 2015, I was working at Diebold where we build ATM machine hardware and software and complete ecosystem around the ATM. When we talk about ATM machine, it is a collection of very complex small hardware which collectively performs tasks. And typically, when we think ATM is only used for cash withdraw and that is not true. When we talk about ATM it is a Bank branch itself. You can deposit cash, withdraw cash, deposit cheques. And Whatever we can do in the branch we can do with…

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…

This article was written by Harshit Sharma.

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…

1.Objective

First of all we will see what is R Clustering, then we will see the Applications of Clustering, Clustering by Similarity Aggregation, use of R amap Package, Implementation of Hierarchical Clustering in R and examples of R clustering in various fields.

2. Introduction to Clustering in…

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…

Imagine yourself the following situation:  You are sitting in a lecture hall, listening to a lecture on mechanics, bored to death, fantasizing the moment you kiss your girlfriend you’ve been dating for the last two months (love is in the air!) Only three more hours to go! Suddenly your i-Relation app sends you the following text: "Hey Josh, watch out! There is a chance of 95% that you are going to have a serious fight with Emily today!" "Oh darn!" you must be…

Summary:  A year ago we wrote about the emergence of fully automated predictive analytic platforms including some with true One-Click Data-In Model-Out capability.  We revisited the five contenders from last year with one new addition and found the automation movement continues to move forward.  We also observed some players from last year have now gone in different directions.  …

This article was written by Hannah Augur.

Global warming. For a topic as massive, important, and (somehow) controversial, big data is a clear option for sorting through the muck. What information is reliable? What solutions are realistic? When a global…

This document comes from Github.

Introduction

tf-seq2seq is a general-purpose encoder-decoder framework for Tensorflow that can be used for Machine Translation, Text Summarization, Conversational Modeling, Image Captioning, and more.

Design…