I came to the Open Developers Conference in Kamata.
Let's create a live article while listening to the story.
** 2017/12/21 postscript ** Click here for presentation slides → https://speakerdeck.com/terapyon/python-ji-jie-xue-xi-kotohazime-at-odc
Predict epidemics from the number of reported influenza in Chiba City and temperature
Received from Chiba City and the Japan Meteorological Agency.
Easy if you come here Immediately
[Shift]-[Enter] will execute
Convenient
You can publish it to github as it is
I can read the bad CSV and process it somehow
Make full use of the data frame function
If you index by date, you can also concatenate weekly data and daily data with a single command.
Serialization
This is the most time consuming
It doesn't work if Japanese is included
You can easily get a histogram from pandas using matplotlib
To define what a "fashion" is
Visualize multivariable calculus at once with pandas The graph that goes straight up from the lower left to the upper right is correlation 1
And
Explanatory variable x
Objective variable y Popular 1 Not popular 0
Save test data to avoid overfitting. 80% for learning, 20% for testing Percentage depends on model and amount of data
use scikit-learn
Use a confusion matrix because it's almost a hit
True positive False positive True negative False negative
Was the ratio of learning and testing OK? Repeat the division and recalculation
(By the way, time runs out
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