All about rotation

ArbitraryAxisRotation/

Softmax function

Graph theory basics

Clique: c undirected and edge between every pair of vertices in the c

Name of the Angles

Know the angle type in Bengali but always confused when comes the english name.
Here it is. There should be no more confusion.

Bayesian Theorm

Marching cube tutorial

Marching cube

4 Dimensional hypercube

Method To Draw A 4-Dimension Cube - The top video clips of the week are here

Talks online

1.99percent
2. ted

Mermaid

Starbuks and Mermaid

MatLab: Study

MATLAB operators:
---------------

1. Colon operator:
---------------
J:K is the same as [J, J+1, ..., K].
J:K is empty if J > K.
J:D:K is the same as [J, J+D, ..., J+m*D] where m = fix((K-J)/D).
J:D:K is empty if D == 0, if D > 0 and J > K, or if D < 0 and J < K.

COLON(J,K) is the same as J:K and COLON(J,D,K) is the same as J:D:K.

The colon notation can be used to pick out selected rows, columns
and elements of vectors, matrices, and arrays. A(:) is all the
elements of A, regarded as a single column. On the left side of an
assignment statement, A(:) fills A, preserving its shape from before.
A(:,J) is the J-th column of A. A(J:K) is [A(J),A(J+1),...,A(K)].
A(:,J:K) is [A(:,J),A(:,J+1),...,A(:,K)] and so on.

The colon notation can be used with a cell array to produce a comma-
separated list. C{:} is the same as C{1},C{2},...,C{end}. The comma
separated list syntax is valid inside () for function calls, [] for
concatenation and function return arguments, and inside {} to produce
a cell array. Expressions such as S(:).name produce the comma separated
list S(1).name,S(2).name,...,S(end).name for the structure S.

For the use of the colon in the FOR statement, See FOR.
For the use of the colon in a comma separated list, See VARARGIN.



2. Matrix transpose operator:
-----------------------
a = ones(1:1:10);
at = a'

' operator transposes a matrix.

3. Details of a variable
------------------
reza = [1]

reza =

1
whos reza

Name Size Bytes Class Attributes

reza 1x1 8 double

4: Cell function:
------------------
    % data_points.labels returns a cell array of +1 and -1
    labels = data_points.label;
    cell_wise_result = cellfun(@(c) find(c == 1), labels, 'uniform', false);
    idx = find(~cellfun(@isempty,  cell_wise_results));

    % updated November, 2018

Computer science ? - Pradipta Sir

Yale Daily News
Published: Monday, January 12, 2009
Kosslyn: Elegance, not tech support
By Justin Kosslyn
The World Beautiful
Computer science is tragically misunderstood. Popular opinion notwithstanding, my
major is not preprofessional.
It does not teach how to fix a printer — though I sometimes wish it did — nor does it
explain why my laptop keeps making disquieting noises. Despite three and a half years of
classes, I have yet to learn how to create a slick Web site or upgrade a hard drive, hack
into servers or configure a firewall. It’s not my fault — none of those topics are in the
computer science curriculum.
What, then, you may wonder, is computer science? It is the study of the structures and the
construction of elegant systems.
Let’s flesh this out. Take Google’s search algorithm as an example. (Full disclosure: I
interned at Google last summer, am currently the campus representative, and will be
returning there next year.) Why did Google beat out AltaVista and all the other early
search engines? Simple: by examining the structure of the World Wide Web.
There is no magic or mystery to the Web’s basic structure, which consists of pages
connected with hyperlinks. If you are reading this online, for example, on the top left of
the page is a large hyperlink to the YDN’s home page. Google’s innovation was to realize
that no page exists in a vacuum, and that by paying attention to the structure of the
hyperlinks — to what was linking where — searches would yield more promising results.
The key to better results was attention to a Web site’s salience — its prominence online
— which is represented as a number from one to 10, known as PageRank. For example,
as of the time of writing, huffingtonpost.com has a PageRank of eight (high salience),
yaledailynews.com has a PageRank of seven, www.yale.edu/rumpus has a PageRank of
five, and thecrimson.com has a PageRank of four (as if we needed Google to tell us that
the YDN is far superior to the Crimson).
Sometimes hyperlinks change. For example, last spring huffingtonpost.com linked to a
number of YDN articles about Aliza Shvarts ’08. Huffingtonpost.com was thereby
effectively endorsing yaledailynews.com. Hundreds of other high-profile external sites
have also linked to the YDN, ranging from Wikipedia to Sports Illustrated. Each of these
mini-endorsements boosts YDN’s PageRank, resulting in the high ranking. And when the
YDN links to another site, some of the YDN’s high PageRank carries over.
You may be surprised by how straightforward this all is. This was a patent-worthy
(number 6,285,999) computer science breakthrough with large practical implications, but
the core of it is exceedingly simple: When important sites link to a new site, the new site
is probably important too. Thus, the quality of Google’s search results arises from the
computer science perspective — understand structure, build elegant systems — applied to
the task of Web searches.
But it is shopping period, and you have a more pressing question at hand: What courses
should you shop? Computer science also has something to say about this kind of
dilemma.
If you really wanted the optimal course list, you might proceed as follows. First,
enumerate aspects of each course: class size, ratings from past years, classroom activities
(discussions, movie screenings, lectures, visiting experts etc.), and so on. Then list out
every course you have taken so far, recording every aspect of each course as well as
whether you enjoyed it.
You — or a computer — are now in a position to build a model of your likes and dislikes,
as well as to understand which dimensions matter more. You may learn, for example, that
having movie screenings significantly boosts your enjoyment of a course while visiting
experts make little difference.
Finally, you can use this understanding to make predictions for the future. By comparing
the predictions against reality, the model can be further refined. In this way you are using
the computer science approach: seeking to understand structure and build an elegant
system to help solve an immediate problem.
This approach can be applied to a wide range of classification problems. For my senior
project, for example, I used a large government database to examine the characteristics of
people at risk of alcohol abuse.
Even if you have no interest in majoring in computer science, a bit of that perspective is
valuable. History, political science, the harder sciences and even literature are replete
with implicit structures that computer science can help frame.
So when you consider the structure of your curriculum this semester, consider computer
science. If you already have a little programming experience — such as programming
your calculator in high school and running analyses in MATLAB or Stata — your course
is Introduction to Computer Science. If you are considering putting a toe in the water for
the very first time, try Introduction to Programming.

And if you need to fix your printer, try calling tech support.

Justin Kosslyn is a senior in Ezra Stiles College.

Michelangelo di Lodovico Buonarroti Simoni: My icon in arts

Michelangelo di Lodovico Buonarroti Simoni (March 6, 1475 – February 18, 1564), commonly known as Michelangelo, was an Italian Renaissance painter, sculptor, architect, poet and engineer. Despite making few forays beyond the arts, his versatility in the disciplines he
took up was of such a high order that he is often considered a contender for the title of the archetypal Renaissance man, along with his rival and fellow Italian Leonardo da Vinci. Michelangelo, who was often arrogant with others and constantly dissatisfied with himself, saw art as originating from inner insp- iration and from culture. In contradiction to the ideas of his rival, Leonardo da Vinci, Michelangelo saw nature as an enemy that had to be overcome. The figures that he created are forceful and dynamic; each in its own space apart from the outside world. For Michel -angelo, the job of the sculptor was to free the forms that were already inside the stone. He believed that every stone had a sculpture within it, and that the work of sculpting was simply a matter of chipping away all that was not a part of the statue.

Though he devoted himself only to sculpture, Michel -angelo never stopped his daily practice of drawing. In his personal life, Michelangelo was abstemious. He told his appr -entice, Ascanio Condivi: "However rich I mayhave been, I have always lived like a poor man." Condivi said he was indifferent to food and drink, eating "more out of necessity than of pleasure" and that he "often slept in his clothes and ... boots." These habits may have made him unpopular; his biographer Paolo Giovio says "His nature was so rough and uncouth that his domestic habits were incredibly squalid, and deprived posterity of any pupils who might have followed him." He may not have minded, since he was by nature a solitary and melancholy person; he had a reputation for being bizzarro e fantastico because he "withdrew himself from the company of men."

Fundamental to Michelangelo's art is his love of male beauty, which attracted him both aesthetically and emotionally. In part, this was an expression of the Renaissance idealization of masculinity. But in Miche -angelo's art there is clearly a sensual response to this aesthetic.^[12] Such feelings caused him great anguish, and he expressed the struggle between Platonic ideals and carnal desire in his sculpture, drawing and his poetry, too, for among his other accomplishments Michelangelo was also a great Italian lyric poet of the 16th century.

List of Michelangelo's work
http://en.wikipedia.org/wiki/List_of_works_by_Michelangelo