2 votes
982 reads

Introduction to Reproducible Analysis - an Interesting Talk by Jeromy Anglim

Jeremy recently had an interesting talk on using R to generate reproducible research. He introduces R markdown and he provides examples of using R Markdown in R Studio. I've embedded the videos in this post. For more information please visit Jeremy's blog here:

Part 1:


2 votes
1106 reads

A brief introduction to Markdown!

Now that Rstudio has released RPubs, R-Studio's phenomenal service to publish documents from R to the web (more info here), a little bit of introduction to markdown, a text to html conversion tool, should be useful. Check out the brief though very useful video below:

2 votes
1621 reads

Google Ngram Viewer: What we learned from 5 million books

"Ngram Viewer" is a tool (in Google Labs) that provides you interesting statistical knowledge of 5 million books (500 billion words) from across centuries. The following video shows how it works. There is a link to the "Ngram Viewer" page.

It might seem simple, but you could still enjoy the power of data analysis revealing some interesting facts (knowledge) about social and cultural phenomena in the history.

3 votes
1241 reads

Reproducible Research and R Workflow - a lecture by Jeromy Anglim

A talk at Melbourne R User Group on Reproducible Research by Jeromy Anglim.

This talk focuses particularly on Eclipse.Jeromy uses a combination of Vim and R for writing Sweave, and Rstudio when he want an IDE experience like Eclipse:

1 vote
1224 reads

Cracking Your Genetic Code (a Worth Watching Video on PBS)

A very interesting video on PBS on "peronalized gene-based medicine".

3 votes
2602 reads

What is the difference between big data and Analytics? O'Reilly's Interview with Jeremy Howard

A very interesting interview with Jeremy Howard on the difference between big data and analytics. Jeremy Howard is Kaggle's president and chief scientist.

Wired Magazine have labeled Jeremy as the accidental scientist. To learn more about Jeremy please read this very interesting article.

4 votes
1399 reads

the data science debate: domain expertise or machine learning?

Strata 2012 had a very interesting debate (watch the debate) on the motion:

"In data science, domain expertise is more important than machine learning skill."

4 votes
1107 reads

Data Sources

Recently, there was post in LDA about Where to find Data? I wanted to add a new source of data to that list. Gapminder is a website (and also a software) with huge amounts of datasets. This site not only allows you to download the data, it also creates nice visual plots and animations of the data.

3 votes
901 reads

Strata 2012: Mike Olson, "Guns, Drugs and Oil: Attacking Big Problems with Big Data"

In Strata 2012 conference, Mike Olson, CEO at CloudEra , talks about "Guns, Drugs and Oil: Attacking Big Problems with Big Data". In the interesting video below, he explains the important role of big data and the very useful insights that can be extracted out of big data. He then introduces Hadoop as an important tool to handle big data.

3 votes
1233 reads

Dealing with structured and unstructured data at Facebook


One of the challenging areas of research is how to deal with unstructured data(like text, comments, videos,…). In the following video, Lars Backstrom is first introducing general trends in Facebook and how they tried to make data more structured in order to use them in different analyses. He also gives some interesting examples of available knowledge hidden in unstructured data in Facebook. Then, he talks about his approach in improving friend recommendation system in the Facebook. 

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