Big Data for Big Brother. Now playing. At a computer near you. How to help water the tree of liberty using statistics?
or
or use SAS software
SAS/CIA from the last paragraph of
Click to access ET_CD_Mumbai_Jul12.pdf
Category: Analytics
Tatvic bets on R
Tatvic, a up and coming startup founded by an ex-Trilogy colleague, has helped with the R for Google Analytics package. While Tatvic is into heavy duty web analytics, they are betting big on R, and using it for Web Analytics. David Smith, most excellent blogger-de-chief in R universe has blogged on them before here http://blog.revolutionanalytics.com/2013/02/analyze-web-traffic-data-with-google-analytics-and-r.html
Here is an upcoming seminar on R in Web Analytics.
Click here
From this webinar, you will get to know:
- What is R and why should you use this tool? How to extract your Web Analytics data into R?
- How to build a predictive model using web analytics data with the help of R?
- How predictive modelling can take your analysis to the next level?
- How to carry out insightful analysis through visualization?
Who should attend: Every web analyst who wants to take his analysis to the next level.
ps- Hat tip to Caroline A
6 weeks Data Scientist Online Courses #rstats
Hosting a 6 weekend live online certification course on Business Analytics with R starting June 1 at Edureka.Check www.edureka.in/r-for-analytics for more details. Course has been decided to ensure more open data science than current expensive offerings that are tech rather than business oriented but more support and customization than a MOOC This is because many business customers don’t care if it is lapply or ddapply, or command line or GUI, as long as they get good ROI on time and money spent in shifting to R from other analytics software.
So many R Packages Everywhere, which one do I use? #rstats
Some thoughts on R Packages
- CRAN is no longer the sole repository for many useful R packages. This includes R Forge, Google Code and increasingly Github
- CRAN lacks the flexibility and social aspect of Github.
- CRAN Views is the only thing that lists subject wide listing of R packages. The categorization is however done more on methods than on use cases or business domains.
- Multiple R packages for the same thing. Which one do I use? Only Stack Overflow helps with that. No rating , no recommendation system
- The packages suggested by R package feature needs better and automatic association analysis . Right now it is manual and dependent on package author and maintainer.
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Quis custodiet ipsos custodes? Who guards the guardians of R packages. In an era of cyber security, we need better transparency on security measures within R packages especially given the international nature of the project. I am very sure I ( or anyone) can create R code to communicate discretely especially on Windows
- I would rather not install anything on my local machine, and read the package directly from the CRAN . CRAN was designed in an era of low bandwidth- this needs to be upgraded.
- Note I am refraining respectfully from the atrocious nature of aesthetics in the home website. Many statisticians feel no use of making R user friendly. My professors at U tenn (from which I dropped out in 2 sems) were horrified when I took courses in graphic design as I wanted to know more on the A and B, which make the A/B testing of statistical design. Now that I am getting older, I get horrified by the lack of HTML, CSS and JQuery by some of the brightest programmers in this project.
- Please comment below.
1-click Random Decision Forests
One of the pitfalls of machine learning is that creating a single predictive model has the potential to overfit your data. That is, the performance on your training data might be very good, but the model does not generalize well to new data. Ensemble learning of decision trees, also referred to as forests or simply ensembles, is a tried-and-true technique for reducing the error of single machine-learned models. By learning multiple models over different subsamples of your data and taking a majority vote at prediction time, the risk of overfitting a single model to all of the data is mitigated. You can read more about this in our previous post.
Early this year, we showed how BigML ensembles outperform their solo counterparts and even beat other machine learning services. However, up until now creating ensembles with BigML has only been available via our API. We are excited to announce that ensembles are now available via our…
View original post 869 more words
A SunBurst of Insight
a nice addition to Big Data Visualization- sunbursts (which I have covered in the Dat Viz chapter of my R book)
Great work by BigML.com
This is a guest post by David Gerster (@gerster), a data scientist and investor in BigML.
I work at a consumer web company, and recently used BigML to understand what drives return visits to our site. I followed Standard Operating Procedure for data mining, sampling a group of users, dividing them into two classes, and creating several features that I hoped would be useful in predicting these classes. I then fed this training data to BigML, which quickly and obediently produced a decision tree:
Next I used BigML’s interface to examine the tree’s many subsets, shown as “nodes” in the diagram above. I moused over a node at the top of the tree and saw that it achieved high separation for a large fraction of the training set:
This one node covered 58% of the data, and separated the two classes with 73% confidence. (“Confidence” is a measure…
View original post 546 more words
Predictive Analytics World goes to Chicago
Message from our Sponsors and my favorite Analytics conference ( only if I could attend a cool analytics conference nearby in Asia (singapore/turkey?) -sighs) Even useR wont come to Asia ever?-
This is the number 1 conference for analytics in the world and it is next month in Chicago, USA? So you think you have the best analytics software or product or service. Here is where you can find it out!
| It’s time to amp-up your analytics strategy. It’s time to beef up your analytics strategy by attending Predictive Analytics World Chicago, June 10-13, 2013. With over 30 case studies from leading organizations across a spectrum of industries, this is the must-attend event for anyone serious about their analytics strategy.
Here’s what your peers had to say about their experience at PAW:
And there is more where that came from. Who’s attending PAW Chicago 2013? Here are just a few of the many companies attending:
And many more! Registration options for all budgets. PAW Chicago has a variety of conference pass options available to meet budgets of all sizes. Learn more about pricing and how to register.
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