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May 2017 Blog Posts (89)

13 Great Articles from AnalyticBridge

AnalyticBridge is one of Data Science Central channels. Below is a selection of popular articles posted a while back:

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Added by Vincent Granville on May 31, 2017 at 8:28am — No Comments

Sentiment Analytics Symposium 2017

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Added by Sunil Kappal on May 30, 2017 at 8:27am — No Comments

Quantum Computing and Deep Learning. How Soon? How Fast?

Summary:  Quantum computing is now a commercial reality.  Here’s the story of the companies that are currently using it in operations and how this will soon disrupt artificial intelligence and deep learning.

 

Like a magician distracting us with one hand while pulling a fast one…

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Added by William Vorhies on May 30, 2017 at 8:00am — 3 Comments

What does it take to be data scientist at Uber

Among the marquee brands that a data science professional would like to join, Uber is likely to be top of many lists. But do you really have what it takes to become a Uberite?

BigInsights Principal Raj Dalal met up with Uber’s Chief Data Architect M C Srivas on a recent…

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Added by Raj Dalal on May 30, 2017 at 2:30am — No Comments

Native Mobile Application Development vs Cross Platform

There are three development approaches: native, cross-platform, and hybrid. Each of them has its own special features, and brings about different results. Not trying to influence your decision as your outsourcing partner and get the ideal for your business product, let's compare all the technologies.

Every day the number of smartphone users keeps growing and world market of mobile apps keeps developing. Every skilled businessman should have already noticed that…

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Added by Alex Black on May 30, 2017 at 1:30am — No Comments

Using R and Google’s keyword planner to evaluate size and competitiveness of international markets

About two months ago there was  new SaaS product, the Keyword Hero. It’s the only solution to “decrypt” the organic keywords in Google Analytics that users searched for in order to get to one’s website. We do so by buying lots of data off sources such as plugins and matching the data with our customers’ sessions in Google Analytics (side note: the entire algorithm was coded in R before we refactored it in Python to allow scalability and operability with AWS).

 

Using Keyword…

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Added by Daniel Schmeh on May 29, 2017 at 10:00am — No Comments

Top Data Analytics Trends for Reatilers of 2017

It’s not easy for a retailer to face ongoing economic challenges. The power of the customers is rising. They have the right to choose the best, and they are not happy with anything less. The competition in every single industry is brutal. We’re not exaggerating when we say that every business battles for survival.



In this war of competitors, data analytics are the most effective weapon. In February 2017, JDA Software Group and PwC (PricewaterhouseCoopers) released…

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Added by Robert Morris on May 29, 2017 at 5:30am — No Comments

Parameter Selection in Classification for Financial Market

In practice, we often have to make parameterization choices for a given classifier in order to achieve optimal classification performances; just to name a few examples:

  • Neural Network: e.g., the optimal choice of Activation Functions, # of hidden units
  • Support Vector Machine: e.g., the optimal choice of Kernel Functions
  • Ensemble: e.g., the number of Learning Cycles for Bagging.
  • Discriminant Analysis: e.g., Linear/Quadratic; regularization…
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Added by Zhongmin Luo on May 29, 2017 at 12:49am — No Comments

Weekly Digest, May 29

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.

Featured Resources and Technical Contributions

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Added by Vincent Granville on May 27, 2017 at 10:30am — No Comments

18 Big Data tools you need to know!!

In today’s digital digital transformation, big data has given organization an edge to analyze the customer behavior & hyper-personalize every interaction which results into cross-sell, improved customer experience and obviously more revenues. The market for Big…
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Added by Sandeep Raut on May 27, 2017 at 5:00am — No Comments

How Data Science apply to Robotics?

Robotics has been and still is an enormous fascination for us humans. Even when we did not have computers, we were fascinated with Mary Shelley's Frankenstein because the concept of creating life out of nothing so resonates with us.…

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Added by Ammar A. Raja on May 26, 2017 at 9:00pm — No Comments

How to Solve the New $1 Million Kaggle Problem - Home Value Estimates

A new competition is posted on Kaggle, and the prize is $1.2 Million. Here we provide some help about solving this new problem: improving home value estimates, sponsored by Zillow. 

We have published in the past about home value forecasting, see here, and also .…

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Added by Vincent Granville on May 26, 2017 at 3:00pm — No Comments

16 Rules that Helped C-Suite Trust Analytics

Guest blog by Manmit Shrimali.

Data science, deep learning, citizen scientists, data lake, big data, AI, machine learning, hadoop, Spark, deep learning....Yes, I get these and breathe them every single day. But let me ask you...Have you been asked any of following questions....

1. As a data scientist, how do you bridge a gap between algorithms and business needs?

2. On…

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Added by Vincent Granville on May 26, 2017 at 1:00pm — 1 Comment

R has a place

I have personally worked in SAS, SPSS and R, and while I agree there are advantages to SAS for example, R has a definite place as free (open source) software with lots of tried and true modules to enable, and easy to access virtually free training via LinkedIn Learning (or Fka Lynda.com). Many small enterprises cannot afford SAS, or the cost of its training, and many large enterprises are trying to force the transition to open source solutions to save money. I have found R extremely easy to…

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Added by Mary Rainer on May 26, 2017 at 10:00am — 1 Comment

Classification with scikit-learn

For python programmers, scikit-learn is one of the best libraries to build Machine Learning applications with. It is ideal for beginners because it has a really simple interface, it is well documented with many examples and tutorials.

Besides supervised machine learning (classification and regression), it can also be used for clustering, dimensionality reduction, feature extraction and engineering,  and pre-processing the data. The interface is consistent over all of these methods, so…

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Added by Ahmet Taspinar on May 26, 2017 at 4:30am — 1 Comment

Big data research paper costs $226 for 30 days access

Out of curiosity, I was checking recent articles published in Journal of the American Statistical Association, as I used to publish in such journals 20 years ago, during my post-doctorate years. I did find some interesting articles, but when I tried to access them, I was asked to fork over $40 to get online access for 24 hours, and $226 to get online access for 30 days.…

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Added by Vincent Granville on May 25, 2017 at 7:30pm — No Comments

17 Great Blogs Posted in the last 12 Months

This is part of a new series of articles: once or twice a month, we post previous articles that were very popular when first published. These articles are at least 6 month old but no more than 12 month old. The previous digest in this series was posted here a while back. 

17 Great Blogs Posted in the last 12 Months…

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Added by Vincent Granville on May 25, 2017 at 1:00pm — No Comments

Artificial Intelligence in Enterprise - Meta-Vision improves outlook and quarterly earnings call for publicly traded companies

Introduction

The quarterly earnings call is a critical event for publicly traded companies. Each call serves multiple purposes. It is both an important source of information for investors and an opportunity for a company to present a narrative of operational performance, financial health, and strategic vision in their own terms. It’s also an ideal opportunity for executives seeking to manage and optimize outcomes.

 

The advent of AI makes it plausible for…

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Added by Sing Koo on May 25, 2017 at 12:30pm — No Comments

Comment on "Why R is Bad for You"

There seems to be a lot confusion about the role of programming in relation to the Data Science platforms that research firms Gartner and Forrester have identified as the future of Data Science in large corporations.  For example, numerous people have stated that SAS is pushing a drag-and-drop platform (Enterprise Miner) that somehow limits choices and is destined to fail due to the fact that using programming (that is, R) allows greater flexibility.

It’s certainly…

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Added by Paul Bremner on May 25, 2017 at 8:30am — 1 Comment

Thursday News: Spatial Data, HDFS, AI, NLP, Anomaly Detection, More AI

Here is our selection of featured articles and resources posted since Monday.

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Added by Vincent Granville on May 25, 2017 at 7:58am — No Comments

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