curiousl: (свинки)
 artstor.org project provides metasearch to numerous first class collections of art, architecture and photo images.
Wannabe single place to search all existing collections, large museums and private collections alike.

The catch is that it is only available to scholars from universities or libraries, but not to general public. In Israel these are TAU, Open University and TA Museum of Art.
Still, they list institutions that cooperate with them and provide metadata about their collection, so one can access original holder of the art work.

The funny thing is that access to the artwork & its data can be gained (at least in some random cases) through proper Google search ...

Btw, tip from Murtha Baca, the metadata name in Getty Institute, is: do use thesauri to arrive at variations of the name for whatever it is you are looking for. Then your favorite search engine will serve you better. 

Of course, Google apparently got its hands on several name authorities, and this is what makes it serve you proper results in all kinds of languages no matter how you typed the name of your favorite artist: in Russian, in French or Italian. By querying the Name Authority relevant to the field they are able to retrieve all possible variations of the name and then search for all of them in the Wild Web ...
And some authorities even have historical names along with current variances of spelling and different languages.
curiousl: (_morda)
 For the first time in a year my  (Metadata) MOOC seems to be extremely relevant to my work. Nice, really.

And all the rest are just being downloaded and archived for later review and study.

Unless some unexpected gem will pop up, next in line will be Statistics, then Data Analysis and Machine Learning. And Computing for Data Analysis at the end. Let's see how realistic is this... I still want to watch movies and read non-tech books. 
curiousl: (_morda)
 interesting place for definitions and classifications of places. It is amazing just how subjective the short "academic" definition might be.
Type in the place (current or historical, political or physical) and watch the Note and Place Type sections. Fascinating reading :).

http://www.getty.edu/research/tools/vocabularies/tgn/?find

Also, they do not have a category under extraterrestrial section that would accommodate ISS, and boy, it is a place where Art is created (and other objects to classify as well). 
curiousl: (Default)
Collection of links to materials suggested by professor and / or fellow students.
Git as a publishing platform is trendy ;).

1. "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming in data analysis with a computation/understanding-first, mathematics-second point of view. All in pure Python 
https://github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers

2. Coursera Data Analysis course (video)  http://www.youtube.com/user/jtleek2007

3. Hypothesis testing and P-value from Khan Academy https://www.khanacademy.org/math/probability/statistics-inferential/hypothesis-testing/v/hypothesis-testing-and-p-values

4. Introduction to Bayes nets http://www.norsys.com/tutorials/netica/secA/tut_A1.htmhttp://www.norsys.com/tutorials/netica/secA/tut_A2.htm

5. Doing Bayesian Data Analysis: a tutorial with R and BUGS http://www.indiana.edu/~kruschke/DoingBayesianDataAnalysis/

6. Bayesian estimation supersedes the t tests. http://www.indiana.edu/~kruschke/BEST/

7. Text classification and naive Bayes (Coursera lecture) https://class.coursera.org/nlp/lecture/37

8. E. Yudkowski An intuitive explanation to Bayes' theorem

9. Positive false discovery rate http://projecteuclid.org/DPubS?service=UI&version=1.0&verb=Display&handle=euclid.aos/1074290335

10. For the old that forgot the school: Udacity course of statistics. https://www.udacity.com/course/st095

11. Data Mining. Practical  machine learning tools and techniques. http://www.cs.waikato.ac.nz/ml/weka/book.html

12 "Probability Theory: The Logic of Science" by E.T. Jaynes tries to give a first principles derivation of statistics (bayesian that is). 

13. http://benmabey.com/2011/10/07/faq-what-machine-learning-book-should-i-start-with.html

14. A practical intro to data science http://blog.zipfianacademy.com/post/46864003608/a-practical-intro-to-data-science

15. DS book and course http://jsresearch.net/wiki/projects/teachdatascience

Illustration: IE use vs Murder rate :)





curiousl: (свинки)
Last night I had a dream. I was wondering about availability of various date formats in MongoDB. The point was that MongoDB native Date type represents both date and time together, while there are lot of applications where time-level precision is not needed. And on a scale MongoDB operates it might be substantial. So the question was if there any native format for date-only. And I hesitated to ask the pros :).
Turned out I actually missed office hours last night - probably the place where it would be appropriate to ask. Looks the dream had some valid cause.
curiousl: (Default)
Network performance evaluation course from a Pakistani professor.
http://youtu.be/rtuf-DZ_CkU

From the list of 20K free university online courses. In a number of engineering, biological and medical fields of knowledge. From India, USA, Italy, ...
curiousl: (Default)
Ну вот, кажется я нашла то самое - возможность неформального дистанционного обучения с полной свободой выбора. Минусов два: не будет диплома и  палки.
Плюсов - все остальное: свобода выбора, уровень преподавания (МИТ как никак, ну и другие, потом, может быть), гибкость в процессе и наконец бесплатность, во!
Пошла составлять программу и заодно осваивать concept maps.

П.С. Музыка Моцарта - единственная совмещается с чтением и немного думанием.

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