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February 2015 Blog Posts (13)

Happy Friday: Three Great Articles for You

Posted today on Data Science Central:

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Added by Vincent Granville on February 27, 2015 at 12:30pm — No Comments

The Imminent Future of Predictive Modeling

Predictive modeling tools and services are undergoing an inevitable step-change which will free data scientists to focus on applications and insight, and result in more powerful and robust models than ever before. Amongst the key enabling technologies are new hugely scalable cross-validation frameworks, and meta-learning.…

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Added by Dr. Justin Washtell on February 26, 2015 at 12:41pm — No Comments

Deep Belief Net with {h2o} on MNIST and its Kaggle competition

In order to evaluate how Deep Belief Net (Deep Learning) of {h2o} works on actual datasets, I applied it to MNIST dataset; but I got the dataset from a Kaggle competition on MNIST so consequently I joined the competition. :P)

As well known, classification tasks such as for MNIST should be…

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Added by Takashi J. OZAKI on February 24, 2015 at 10:30pm — No Comments

Reading selection for the weekend

These are some of the articles that will appear in our DSC Monday digest.

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Added by Vincent Granville on February 21, 2015 at 4:00pm — No Comments

Random Walks or Fractal Matters

Much has been said about random walks, mostly in the form of bringing up the term and not caring to define precisely what "random" means. Barring those cases when "stochastic" and "random" are used interchangeably, true randomness implies absence of any order definable by the brain (see also psychology's contributions to creative personality and random number generation).

But since any numerical structure is a derivative of an underlying quantity evaluation system (e.g. number…

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Added by Mortal Kolle on February 20, 2015 at 12:00am — No Comments

PythoneeR

After using a lot of R for analytics projects believing that it was the best language for Data Scientists, I recently had the chance to pick up Python. R does seem a bit cumbersome when dealing with interfaces to other languages or to the web such as oauth. That was my motivation, to use Python to get text from the web and later process it in R, which was, I felt the "best" tool to go about.

However, Python surprised me not only with it's web interfacing abilities, but also…

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Added by Amogh Borkar on February 18, 2015 at 10:20pm — 2 Comments

Overheating of "Artificial Intelligence" boom in Japan, while "Data Scientist" is fading out

Currently I'm concerned about incredible overheating of "Artificial Intelligence" boom in Japan - while "Data Scientist" has gone.

Google Trends shows Japanese people are getting just less attracted by statistics that is believed to be expertise of Data Scientist, and now they are enthusiastic about Artificial Intelligence. I feel this situation looks much puzzling.

So, what's going on in 2015?... yes, I think not a few data science experts in Japan must agree that "Artificial…

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Added by Takashi J. OZAKI on February 18, 2015 at 8:00am — No Comments

Experiments of Deep Learning with {h2o} package on R

Below is the latest post (and the first post in these 10 months...) of my blog.

What kind of decision boundaries does Deep Learning (Deep Belief Net) draw? Practice with R and {h2o} package

Once I wrote a post about a relationship between features of machine learning classifiers and their decision boundaries on the same dataset. The result was much interesting and many people looked to enjoy and even argued about it.

Actually I've been looking for similar…

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Added by Takashi J. OZAKI on February 15, 2015 at 3:30am — No Comments

Friday reading

We are getting closer to having a nice search functionality on DSC. If you remember the title of one of our articles - or some keywords - but can't find it on Google, try our DSC search engine. You can find the Search tab at the top, on any web page on our network. This search functionality is now ads-free.

Also, we are in the process of writing an article Data scientist shares his growth hacking secrets, which we expect to…

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Added by Vincent Granville on February 13, 2015 at 12:30pm — No Comments

SuperBowl XLIX in Tweets: Sentiment Analysis of 4 Million Tweets

This blog was originally published on our Text Analysis blog, the blog post set out to analyze and visualize 4 million tweets collected during Superbowl XLIX. Not surprisingly, Superbowl XLIX generated a huge amount of chatter on social networks with Twitter Estimating that over 28.4 million posts made with terms relating to the Superbowl.

At AYLIEN, we collected…

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Added by Mike Waldron on February 9, 2015 at 10:00am — No Comments

Four great visualizations

We actually have three posts to share with you today:

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Added by Vincent Granville on February 6, 2015 at 1:30pm — No Comments

Data Analysis with Pandas

Python has become the language of choice for a lot of statisticians and data scientists. The main driving force behind Python’s adoption among data scientists is the Pandas, the open source library tool in of Python.

Here are some features of the library:

  1. A fast and efficient DataFrame object for data manipulation with integrated indexing;
  2. Tools for reading and writing data between in-memory data structures and different formats: CSV and…
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Added by Vincent Granville on February 2, 2015 at 3:30pm — No Comments

Digital Banking – Lessons from channel integration

Digital banking offers unprecedented opportunities both for banks as well as customers. It has provided banks breadth and ease in delivering their products and services to customers. As for customers, it has pushed service options and expectations to a new high. Given the opportunity spectrum, it is no surprise that banks have invested heavily in upgrading their digital preparedness. 2015 promises more investments in digital banking.

A definition of digital banking will be of help…

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Added by Naagesh Padmanaban on February 2, 2015 at 12:00am — No Comments

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