Masaki Takahashi startselect

## Yokohama deep learning 03
import numpy as np

class Neuron:
    def __init__(self, w, b, f):
        self.w = np.concatenate((w, b), axis =1)
        self.f = f

    def output(self, x):
        x = np.concatenate((x, [[1,],]))
        return self.f(self.w.dot(x))

## mps_pacman_03
<!DOCTYPE html>
<html lang="ja">
<head>
    <meta charset="utf-8">
    <title>JS_PacMan 3</title>
</head>
<style type="text/css">
#pacman {
    background-color: #fff;
}

## pacman02
<!DOCTYPE html>
<html lang="ja">
    <head>
        <meta charset="utf-8">
        <title>JS_PacMan</title>
    </head>
        <style type="text/css">
        #pacman {
            background-color: #fff;
        }

## pacman01setagaya
<!DOCTYPE html>
<html lang="ja">
    <head>
        <meta charset="utf-8">
        <title>PacMan</title>
    </head>
        <style type="text/css">
        </style>
    <body>
        <canvas id="pacman" width="300" height="150">
	import numpy as np

	class Neuron:
	def __init__(self, w, b, f):
	self.w = np.concatenate((w, b), axis =1)
	self.f = f

	def output(self, x):
	x = np.concatenate((x, [[1,],]))
	return self.f(self.w.dot(x))
	<!DOCTYPE html>
	<html lang="ja">
	<head>
	<meta charset="utf-8">
	<title>JS_PacMan 3</title>
	</head>
	<style type="text/css">
	#pacman {
	background-color: #fff;
	}