Louis Aslett makes data science on the cloud a 2 click step away

I was having a few issues with trying to configure the latest version of RStudio Server and the free help was not helpful enough. I came to this wonderful site and it made my job on running R on the cloud for students just a 2 click step. The best thing is lots of goodies come pre-installed.

http://www.louisaslett.com/RStudio_AMI/

Why an RStudio AMI?

The RStudio team have done a phenomenal job with making it simplicity itself to install, but there are still several motivating factors which led to me creating this AMI:

  • Although simple, it still takes several minutes to install R and RStudio after the virtual machine is going and this adds up if you do it often.
  • More time consuming is getting all the extras one may want such as LaTeX, Git, etc installed.
  • Of course, ‘simple’ is subjective and there are those who don’t know Linux, but want to use RStudio on a server without ever touching a Linux command line.
  • The EBS-backed AMIs with operating systems on tend to have vast swathes of free space which (as a postdoc of modest means) I don’t like paying to store when putting a machine into a stopped state for hibernation between computational runs! Growing an EBS volume is easier than shrinking one, so having a minimally sized AMI ready-to-go saves effort.
  • Having the full tool stack through to linking a Dropbox account in about 5 seconds means that I can go from zero to having a 36-core machine with over 200GB of RAM with all my code and data synced to a fully functional R environment with all supporting tools in a matter of minutes.
  • At the time of writing I couldn’t find any with the standard Amazon search tools and — in the great open-source tradition — that seems like an itch I should scratch!

Screenshot from 2015-09-08 13:12:48

 

Moving my Meetup Group to a Facebook Group

I am moving the 657 member Meetup Group New Delhi R Users Group

Screenshot from 2015-09-06 15:56:56to the Facebook Group New Delhi R Users Group https://www.facebook.com/groups/865780260143073/

https://www.facebook.com/groups/865780260143073/

Screenshot from 2015-09-06 15:55:17

 

 

I dont see the point of paying 30 $ every six months for an obsolete design when FB groups are more free and more easy to operate.  Privacy guidelines and spam control is just a button away on FB. LinkedIn groups are even more different.

Sponsored Post: Wise Practitioner – Predictive Analytics Interview Series: Herman Jopia of American Savings Bank

A blog post from our sponsors in the once a month series-

Original article on

http://www.predictiveanalyticsworld.com/patimes/wise-practitioner-predictive-analytics-interview-series-herman-jopia-of-american-savings-bank07152015/

In anticipation of his upcoming conference presentation,Driving Superior Growth Through Self-Developed Code, Scoring Modeling, and Price Optimization, at Predictive Analytics WorldHerman_JopiaBoston, Sept 27-Oct 1, 2015, we asked Herman Jopia, First Vice President and Data Analytics Manager at American Savings Bank, a few questions about his work in predictive analytics.

Q: In your work with predictive analytics, what behavior do your models predict?

A: We have developed and implemented attrition, profitability, and response models.

Q: How does predictive analytics deliver value at your organization? What is one specific way in which it actively drives decisions?

A: Predictive analytics helps us to understand our customers and prospects.  In practice that means a better answer to questions like who to target,  what to offer, why it makes sense, and when and how to do it.  For example, our response model for direct mail helps us to manage volume and reduce costs by excluding prospects that have a low propensity of taking the offer; therefore, it drives a lift on our profitability metrics.

Q: Can you describe a successful result, such as the predictive lift of your model or the ROI of an analytics initiative?

A: Besides monitoring the models and metrics, we actually look at how these models impact both growth and profitability.  For example in 2014 our targeted direct mail offers dramatically increased the volume and ……

Read the complete article at

http://www.predictiveanalyticsworld.com/patimes/wise-practitioner-predictive-analytics-interview-series-herman-jopia-of-american-savings-bank07152015/

Trying to improve the supply of Data Scientists without ripping young people

In a previous post, I said that many corporate are trying to benefit from the demand for data science as applied to their sector or company but not many are doing enough to improve the supply of data scientists.

demand

In anecdotal arguments for students In India and USA , many have  argued that many training companies are charging exorbitant amounts and misguided promises to essentially teach tools and techniques but not the essential analytical mindset for splicing and dicing of data as well as enough information to reach balance between the three skills for data scientists- statistics, programming and business perspective.

Added to this, many people building tools for data scientists have not worked in data science consulting them self but are addicted to one platform or product due to commercial or intellectual compulsions.

BdoZ6NjIcAAGv3w

Here is what I think could be a supply side solution to the problem of demand of data scientists hindering actual data science benefits to humanity regardless of commercial or social sectors.

  1. Build up a pool of curated best practice training
  2. Get them validated and verified across different business sectors by industry experts
  3. Add hardware or cloud training to software training
  4. Offer them on accessible platforms like mobile, tablet and web
  5. Offer them on accessible languages like Spanish Swahili Chinese Arabic as well
  6. Gamify some of the content to make it interesting, basically start creating data science hackers at an earlier age than just post graduate students
  7. Tie up with industry to offer internships that are fair balanced and demand equal commitment
  8. Tie in soft skill training for better professionalism
  9. Offer all this for free but use data generated for improving this not only on a human intervention basis but computer adaptive training and testing
  10. Monetize only after you reach a huge scale not prematurely
  11. Make it interactive using videos, 15 minute weekly personalized help on Skype from support, webinars but capture data continuously to drive engagement metrics

Do you want to just make money on the demand (uncertain) for data science but do you want to make more money on the supply side of data science too?

bor66

Social Media Networking for Data Scientists Top Groups On LinkedIn Facebook Twitter and Google Plus

A list of places on the Internet where you want to hang out if you want to build your name, fame as well as read and share content for data science and big data analytics

Do you want to add a list or group- just put it on comments on DecisionStats.com post

(list compiled by our Data Science Intern, Prerna Sahay)

 

Facebook Groups:

  1. Analytics, data mining, predictive modeling, big data

(https://www.facebook.com/groups/data.analytics/ )

  1. Apache Hadoop (https://www.facebook.com/groups/158386177549436/ )
  1. Apache Hadoop Ecosystem (https://www.facebook.com/groups/hadoop.group/ )
  1. Big Data (https://www.facebook.com/groups/BigDataisonline/ )
  1. Big Data Analytics using R (https://www.facebook.com/groups/434352233255448/ )
  1. Big Data Analytics with R and Hadoop (https://www.facebook.com/groups/rhadoop/ )
  1. Big Data Hadoop NOSQL Hive Hbase (https://www.facebook.com/groups/bigdatahadoop/ )
  1. Big Data Learnings (https://www.facebook.com/groups/bigdatalearnings/ )
  1. Big Data Malaysia (https://www.facebook.com/groups/bigdatamy/ )
  1. Big Data , Data Science , Data Mining & Statistics (https://www.facebook.com/groups/bigdatastatistics/ )
  1. BigData/Hadoop Expert (https://www.facebook.com/groups/BigDataExpert/ )
  1. Chennai Hadoop and Big Data User Group (https://www.facebook.com/groups/chennaihadoop/ )
  1. Data Mining / Machine Learning /AI (https://www.facebook.com/groups/machinelearningforum/ )
  1. Data Mining/ Big Data (https://www.facebook.com/groups/dataminingsocialnetworks/ )
  1. Hadoop Administrators (https://www.facebook.com/groups/hadoop.admins/ )
  1. Hadoop Developers India (https://www.facebook.com/groups/423391947699826/ )
  1. Hadoop in Action (https://www.facebook.com/groups/haddopinaction/ )
  1. Hadoop Jobs (https://www.facebook.com/groups/hadoopjobs/ )

 

  1. Hadoop Material (https://www.facebook.com/groups/416616701771842/ )
  1. Hadoop User Group (https://www.facebook.com/groups/hadoopcrunch/ )
  1. Tackling the Challenges of Big Data

(https://www.facebook.com/groups/tcobd/?ref=browser )

  1. MapReduce (https://www.facebook.com/groups/mapreducegroup/ )
  1. Tableau Software User Group (https://www.facebook.com/groups/181682408543566/ )
  1. Spotfire Group (https://www.facebook.com/groups/766623530030197/ )
  1. Hadoop Big Data- The next Big Thing (https://www.facebook.com/groups/hadoop.big.data/ )
  1. Coursera (https://www.facebook.com/groups/CourseraConnections/?ref=browser )

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Linkedin Groups:

  1. KDnuggets Analytics, Data Mining and Data Science (https://www.linkedin.com/grp/home?gid=54257 )
  2. Cloud Computing (https://www.linkedin.com/grp/home?gid=61513 )
  3. Quantitative Analysis Professional (https://www.linkedin.com/grp/home?gid=71149 )
  4. Online Data Visualisation (https://www.linkedin.com/grp/home?gid=3707334 )
  5. Big Data and analytics (https://www.linkedin.com/grp/home?gid=4332669 )
  6. Data Scientists (https://www.linkedin.com/grp/home?gid=2013423 )
  7. Predictive Analytics Network (PAN) (https://www.linkedin.com/grp/home?gid=1849479 )
  8. Data Mining Pioneers (https://www.linkedin.com/groups/Data-Mining-Pioneers-64585/about )
  9. Big Data | Analytics | Strategy | Finance | Innovation (https://www.linkedin.com/grp/home?gid=1814785 )
  10. Business Intelligence and Analytics (3527380) (https://www.linkedin.com/grp/home?gid=3527380 )
  11. Indian Internet of Things (IIoT) (https://www.linkedin.com/grp/home?gid=8198420 )
  12. Big Data , Analytics , Business Intelligence & Visualization Experts Community (https://www.linkedin.com/grp/home?gid=23006 )
  13. Data Science , Big Data and Analytics Executives (https://www.linkedin.com/groups/Data-Science-Big-Data-Analytics-5074372/about )
  14. People Learning R (https://www.linkedin.com/grp/home?gid=5150073 )
  15. Predictive Analytics World (https://www.linkedin.com/grp/home?gid=1005097 )
  16. Springer Network (https://www.linkedin.com/groups/Springer-Network-29206/about )
  17. India Analytics Network (https://www.linkedin.com/grp/home?gid=1858675 )
  18. RDataMining: R and Data Mining (https://www.linkedin.com/grp/home?gid=4066593 )
  19. Business Intelligence
  20. R/Finance (https://www.linkedin.com/grp/home?gid=155029 )
  21. Big Data, Analytics and Data Science Training (https://www.linkedin.com/grp/home?gid=4989164 )
  22. R Developers and Users Group (https://www.linkedin.com/grp/home?gid=3740742 )
  23. Information Security Community (https://www.linkedin.com/grp/home?gid=38412 )
  24. Predictive Model Markup Language (PMML) (https://www.linkedin.com/grp/home?gid=2328634 )
  25. The R Project for Statistical Computing (https://www.linkedin.com/grp/home?gid=77616 )
  26. Spotfire User Group – SFUG for Spotfire Analytics Developers , Enthusiasts and Practioners (https://www.linkedin.com/grp/home?gid=3984312 )
  27. Spotfire Developers , Consultants and Partners (https://www.linkedin.com/groups?gid=2480584 )
  28. Spotfire Enthusiasts (https://www.linkedin.com/grp/home?gid=3752855 )
  29. Machine Learning Connection (https://www.linkedin.com/groups?gid=70219)
  30. SAS Analytics & BI (https://www.linkedin.com/groups?gid=130238 )

Twitter # Tags:

  1. #rstats (https://twitter.com/search?q=%23rstats )
  2. #datascience (https://twitter.com/hashtag/datascience?src=rela )
  3. #bigdata (https://twitter.com/hashtag/bigdata?src=rela )
  4. #iot (https://twitter.com/hashtag/iot?src=rela )
  5. #bigdata (https://twitter.com/hashtag/bigdata?src=rela )
  6. #analytics (https://twitter.com/hashtag/analytics?src=rela )
  7. #internet of things (https://twitter.com/hashtag/internetofthings?src=rela )
  8. #tableau (https://twitter.com/search?q=%23tableau)
  9. #dataviz (https://twitter.com/hashtag/dataviz?src=rela )
  10. #machinelearning (https://twitter.com/hashtag/machinelearning?src=rela )
  11. #spotfire (https://twitter.com/search?q=%23spotfire)
  12. @tibco (https://twitter.com/search?q=%40tibco )
  13. #businessintelligence (https://twitter.com/search?q=%23businessintelligence )
  14. #deeplearning (https://twitter.com/search?q=%23deeplearning )
  15. #ai (https://twitter.com/hashtag/ai?src=rela )
  16. #hadoop (https://twitter.com/search?q=%23hadoop )
  17. #cloud (https://twitter.com/search?q=%23cloud )
  18. #python (https://twitter.com/search?q=%23python )
  19. #django (https://twitter.com/search?q=%23python )
  20. #statistics (https://twitter.com/search?q=%23statistics )

Google plus communities:

  1. Data Science – Data , Knowledge, Action (https://plus.google.com/u/0/communities/104673320232127474190 )
  2. Big Data – Big Questions? Big Data = Big Answers (https://plus.google.com/u/0/communities/118194042397414247987 )
  3. Data Science – making big data small (https://plus.google.com/u/0/communities/113253740387558560113 )
  4. Machine Learning – The beauty of the artificial mind (https://plus.google.com/u/0/communities/101342316728284418850 )
  5. Hadoop – Articles , discussion and learning (https://plus.google.com/communities/105735667520214958344 )
  6. Google Analytics – The largest GA user community (https://plus.google.com/communities/114481059214254340537 )
  7. Statistics and R – interested in R and statistics? Join us! (https://plus.google.com/communities/117681470673972651781 )
  8. Python – Unofficial Python Community (https://plus.google.com/communities/103393744324769547228 )
  9. Machine Learning – The beauty of the artificial mind (https://plus.google.com/communities/101342316728284418850 )
  10. Machine learning , IR , Mining , Big Data – ML,IR,KDD,Big Data Mining,Search,Social Networks (https://plus.google.com/communities/112064568745102322361 )
  11. Machine Learning – Academia , Industry and anyone who has an interest on ML and Data (https://plus.google.com/communities/107785538899595981479 )
  12. Big Data – Big Data , Analytics and Data Science (https://plus.google.com/communities/107156514183161811383 )
  13. Big Data professionals – This G+ page is for everyone involved in the development of applications using Big Data. Innovate together with Big Data professionals!

(https://plus.google.com/communities/101646309652442505961 )

  1. Big Data. Artificial Intelligence. Bi. – Internet of Things / IoT / M2M / Machine Learning ▪ Crypto Currencies ▪ Bitcoin ▪ Artificial Intelligence ▪ Digital Currencies (https://plus.google.com/communities/114206007718004250940 )
  2. Big Data – Exploring how big data is changing the world (https://plus.google.com/communities/109707855685220573696 )
  3. Big Data R&D – (https://plus.google.com/communities/103487294531677099010 )
  4. Big Data, Economy & Technology – Checking innovations and using Data to build efficient decision platforms and amazing visualizations. (https://plus.google.com/communities/104041697322064738236 )
  5. Business Intelligence – Big Data, Data Visualization, Actionable Insights, Software, Tools & Solutions (https://plus.google.com/communities/110061721590251903650 )