Artificial Intelligence Study the step-by-step codes for a one layer o.pdf
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Artificial Intelligence Study the step-by-step codes for a one layer of Convolution (with given padding and stride) followed by pooling layer and ReLU (written in NumPy of Python): https://github.com/Kulbear/deep-learning- coursera/blob/master/Convolutional%20Neural%20Networks/Convolution% 20model%20-%20Step%20by%20Step%20-%20v1.ipynb Then write a simple code that does the forward path of a CNN (two layer of Convolution/Pooling/ReLU) followed by one layer of Fully Connected Network. Preferred code is Python.
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{
public:
float red, green, blue;
float x, y, width;
BRICKTYPE brick_type;
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float red, green, blue;
float radius;
float x;
float y;
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#include <GLFW\glfw3.h>
#include "linmath.h"
#include <stdlib.h>
#include <stdio.h>
#include <conio.h>
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#include <vector>
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enum ONOFF { ON, OFF };
class Brick
{
public:
float red, green, blue;
float x, y, width;
BRICKTYPE brick_type;
ONOFF onoff;
Brick(BRICKTYPE bt, float xx, float yy, float ww, float rr, float gg, float bb)
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double halfside = width / 6;
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{
public:
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float radius;
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float y;
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blue = b;
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direction = GetDirection();
x = x + 0.01;
y = y + 0.02;
}
}
else if (brk->brick_type == DESTRUCTABLE)
{
if ((x > brk->x - brk->width && x <= brk->x + brk->width) && (y > brk->y - brk->width
&& y <= brk->y + brk->width))
{
brk->onoff = OFF;
}
}
}
int GetDirection()
{
return (rand() % 8) + 1;
}
void MoveOneStep()
{
if (direction == 1 || direction == 5 || direction == 6) // up
{
if (y > -1 + radius)
{
y -= speed;
}
else
{
direction = GetDirection();
}
}
if (direction == 2 || direction == 5 || direction == 7) // right
{
if (x < 1 - radius)
{
x += speed;
}
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{
direction = GetDirection();
}
}
if (direction =.
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P Q s
$100 100
$103 101
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Chapter 2
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