9 Minutes Introduction Video to Agile Scrum Method

Brilliant compact explanation about agile scrum software engineering method by Hamid Shojaee.



note: I do not own the video for sure ;)

The Innovation of Loneliness - Vimeo Video

I find that this great video by Shimi Cohen below has some truth in it.  Many modern people, especially the youngsters, have lost the sense of real life social interaction in exchange for the convenience that digital artificial social media offers.

Come on people, meet real people, and interact with them.  Spend less time in interacting with your PC/ laptop/ smart-phone which gives the sensation of artificial connectivity :p

Software Release Management - Scanned Notes

Conserving some knowledge from my old note book should not be a bad idea...

 

... for some notes, it's better than throwing them directly to the trash can.

Reviewing Machine Learning (Prediction Model) Diagnostics

Suppose, you've done all you need to do to build a prediction model.  Despite your hard work and high expectation, the prediction model you've designed performs poorly.

What to do next then?

After having a discussion with a good friend, he suggested me to review Andrew Ng's advices for debugging predictive analytic (machine learning) model.  He referred me to the video series below:



Having all the videos in the series (Advice for Applying Machine Learning - What to Do Next 1-7) reviewed , I learned about the machine learning diagnostic issue.  To Andries Ng's words, machine learning diagnostics is defined as: "a test that you can run to gain insight what is/isn't working with a learning algorithm and gain guidance as to how best to improve its (predictive) performance." 

Machine learning diagnostics is built on the identification of "bias" and "variance" symptoms of predictive models.  Based on the symptom's identification process, we can then define the prospective measures that will likely lead to better result.

So, what to do next then?
Based on the advice from lecture sets, the alternative measures are:

 ... and back to work, for sure :p 

Free Statistical Machine Learning Books and Lecture Slides

Statistical Machine Learning - Data Mining - Business Intelligence Books.

Inspired by recent David Smith's blog post about the possibility to downloading free Statistical Machine Learning e-book, I try to "re-echo" and "re-package" the exciting news.  Thanks to the generous researchers who make their valuable works freely available, we can download free digital copy of their books (either whole or as subsections) and the accompanying lecture slides.  Herewith, I list the URLs for downloading some data mining/ predictive analytic/ statistical machine learning resources

1.  "Elements of Statistical Learning (Full Book)" by  Trevor Hastie, Robert Tibshirani, and Jerome Friedman.

2.  "Information Theory, Inference, and Learning Algorithm (Full Book)" by David MacKay.

3.  "Forecasting: Principles and Practices (Full Book)" by Rob J Hyndman and George Athanasopoulos.

4.  "Introduction to Data Mining (3 Chapters of the Full Book and Complete Lecture Slides)" by Pang-Ning Tan, Michael Steinbach, and Vipin Kumar.

5.  "Machine Learning (Lecture Slides)" by Tom Mitchell.

6.  "Pattern Recognition and Machine Learning (one Sample Chapter and Some Lecture Slides)" by Christopher Bishop.

7.  "Data Mining for Business Intelligence (Instructor Materials)" by Galit Shmuelli, Nitin Patel, and Peter Bruce.

(the following URLs do not really fits in the data analytics topic, but they're useful information to share anyway:D).

8.  "Multiagent Systems - Algorithmic, Game-Theoric, and Logical Foundations (Full Book)" by Yoav Shoham and Kevin Leyton Brown.

9.  "Fundamentals of Multiagent Systems with NetLogo Examples" by Jose M Vidal.

10.  "Essential of Metaheuristics (Full Book)" by Sean Luke.


Hopefully the URLs will still work in the future,  Enjoy then.. :)

Knowing Extra Data Analytic Tools can be Handy

In the last period, I have been using R for preparing and analyzing big sized data.  It has been a reliable tool for many of my needs.  The existence of numerous blogs (e.g. r-bloggers) that share many useful tips makes trouble shooting can be done reasonably fast.

Memory Allocation Notification - R

Not without flaw, I just realized that R does have its limit.  At the moment, it can not allocate working memory more than 2.2 GB regardless how powerful your computer is (see the description picture above).  Although you have 8 GB RAM, R will send an exception when the utilized memory reaches the allowed limit.  To solve this issue (i.e. coping with "big data" analysis using R) Ryan Rosario's video can stand as a good reference.

EM Clustering - Weka

I haven't really experimented with what the video has suggested (I am not in the mood for learning new package :p).  In exchange, for my problem at the time (doing EM clustering for ~25,000 records data), I just used my old "fellow" Weka, and solve the problem within 30 minutes or so.

Because a tool's limitation can be explored at unexpected time, it is always handy to know more than one statistical learning tools (e.g. R, Weka, Rapidminer, etc).  Happy data crunching then :).  

Network Plot with Gephi - My 1st Trial

After quite sometime from my initial blog about Gephi, finally I took some time to learn using it.  Actually, for few days I've been trying to find some available network plot packages that can be developed within R environment.  However I can't find one that can produce appealing visualization better than Gephi (at least for now).  For those of you who'd love to learn making network plots using R, I do recommend Dai Shizuka's blog for clear starter tutorials.  For those who want to learn Gephi, it will take you about one or two days to make descent graphs.  Gephi is quite easy to learn for a beginner.  In principle, I only need to read two guides (i.e. the quick start guide and the supported input files) to start.  For making a try out plot (below) I spent most of the time in preparing the edge list input file.  So give some time to try it yourself then... :)     

My First Gephi Plot.

Schiphol Airport's Luggage Logistics

When I was clearing up some old magazines and papers,  I realized an interesting information was hiding in one of the magazines.   I ripped some of the pages and scanned them to "conserve" the insight about how the Schiphol Airport (one of the world's busiest airports) handle an important issue of any traveler, the luggage business (can you imagine if you arrive in another continent without finding your luggage at the picking belt? surely it will be disastrous!!!).   Investing one or two minutes to understand how they handle our precious bags won't hurt.   Anyway its better to keep the insight in this blog rather than junk it directly to the trash can for sure.

The information source is the Schiphol Magazine - September 2011,  I think I intentionally brought the magazine with me along the traveling to scan the luggage operation description.   After more than a year, I did scan them today..  better late than never huh.. :p

Click on the picture for better viewing and enjoy!!!

Luggage Logistics Operation - Page 1

Luggage Logistics Operation - Page 2

Luggage Logistics Operation - Page 3

Luggage Logistics Operation - Page 4

2012 Berganti 2013: Kliping Foto Kalender Belanda

2012 beranjak pergi, 2013 menghampiri tak terhindari..  semoga dalam setiap periode waktu, entah itu detik baru, menit baru, jam baru, hari baru, minggu baru, bulan baru, ataupun tahun baru, kita selalu belajar dan berada dalam derajat kebaikan yang lebih bagus dari masa-masa yang telah lampau.. (amin :p)

Kelender 2012

Seru-seruan nge-scan kalender 2012 yang dikasih gratis dari yang punya kontrakan, sayang juga kalau harus berakhir di tempat sampah gambar-gambar bagusnya.  Seru juga untuk ngehias blog di awal tahun ini :D

Negeri Belanda

Paul Arden Trilogy

Finally, ...
... after a year I've managed to complete the Paul Arden's trilogy by getting the "It's not how good you are, It's how good you want to be (IsnhgyaIshgywtb)".

Content-wise, the message of the book is pretty much similar with the one of "Whatever you think, think the opposite (wyttto)".  The IsnhgyaIshgywtb is more aimed for the reader with advertising industry background while the wyttto is open for any people.  I like the wyttto better.  Maybe because it was my first book from Arden.

Anyway, its good to have all of the three in my collections.

 So...  

... I have decided that the most recommended one should be "Whatever you think, think the opposite", the second most recommended one should be
"It's not how good you are, It's how good you want to be", and last but not least, its also recommended to complete your collection with "God explained in a taxi ride" (not) only for the sake of the trilogy completion off course ;).