s4nyam

['magma',
 'inferno',
 'plasma',
 'viridis',
 'cividis',
 'twilight',
 'twilight_shifted',
 'turbo',
 'Blues',
 'BrBG',

s4nyam

import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from matplotlib.animation import FuncAnimation

def ackley(x, y):
    a = 20
    b = 0.2
    c = 2 * np.pi
    term1 = -a * np.exp(-b * np.sqrt((x**2 + y**2) / 2))

s4nyam

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation

def fitness(x, y):
    return np.sin(x) * np.cos(y)

mutation_range = 0.02

population = np.array([[np.random.uniform(-5, 5), np.random.uniform(-5, 5)]])

s4nyam

import pygame
import numpy as np


# Setting parameters
width = 100
height = 100
cell_size = 15
spacing = 2
live_color = (0, 150, 0)

s4nyam

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
from matplotlib.animation import PillowWriter

# Define the initial state of the grid
grid = np.zeros((100, 100))
grid[1, 2] = 1
grid[2, 3] = 1
grid[3, 1:4] = 1

s4nyam

import pygame
import random

# Set up the Pygame window
pygame.init()
screen = pygame.display.set_mode((800, 600))
pygame.display.set_caption("Northern Lights")

# Define some colors
black = (0, 0, 0)

s4nyam

Deep Learning for Face Recognition (May 2016)

Popular architectures

• FaceNet (Google)
  • They use a triplet loss with the goal of keeping the L2 intra-class distances low and inter-class distances high
• DeepID (Hong Kong University)
  • They use verification and identification signals to train the network. Afer each convolutional layer there is an identity layer connected to the supervisory signals in order to train each layer closely (on top of normal backprop)
• DeepFace (Facebook)
  • Convs followed by locally connected, followed by fully connected

s4nyam

# import the necessary packages
import argparse
import datetime
import imutils
import time
import cv2
from facerec.feature import Fisherfaces
from facerec.classifier import NearestNeighbor
from facerec.model import PredictableModel