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This part is heavily adapted from Johnson's talk in DSP.
What can you find from this helicop for car chasing video?
The wave pattern turns out to be some data coding, with most part repeating. Location? Video timestamp? Camera direction?
Map full trace on map. Later decodes into exact GPS locations
Anyway, that is pretty much how to conduct a data analysis
We then dive into each following subjects one by one.
And best place to learn data science as well
Check out http://g0v.tw/
Heavily utilized "Human Learning" (工人智慧) How?
Using Hough Transform in OpenCV
Divide the table by separate cells
Seems just crawling data, what's special?
Statistics is about
model.full <- lm(Speed ~ HP_10 * Time, data=df_sim) model.hi <- update( model.full, . ~ . + HP_10 : I(Time^2), # try `HP_10 * I(Time^2)` data=df_sim ) anova(model.full, model.hi) summary(model.hi)
anova(...) # Analysis of Variance Table # # Model 1: Speed ~ HP_10 * Time # Model 2: Speed ~ HP_10 + Time + HP_10:Time + HP_10:I(Time^2) # Res.Df RSS Df Sum of Sq F Pr(>F) # 1 474 269.43 # 2 472 242.26 2 27.175 26.473 1.269e-11 *** summary(...) # Coefficients: # Estimate Std. Error t value Pr(>|t|) # (Intercept) 10.09593 0.10485 96.289 < 2e-16 *** # HP_101 3.87381 0.15231 25.433 < 2e-16 *** # Time 0.06238 0.14318 0.436 0.663 # HP_101:Time -0.94099 0.20679 -4.551 6.81e-06 *** # HP_100:I(Time^2) -0.18324 0.03914 -4.681 3.73e-06 *** # HP_101:I(Time^2) 0.23082 0.04143 5.571 4.27e-08 ***
... WAIT! Are you sure that's the article about?
With today's method, we can reveal more details, provide different view points, and can be fancier :)
Web and browsers dominates our front-end world.
Almost every PC and mobile have a modern browser today.
← SVG / HTML5 Canvas
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