victor-iyi

#!/usr/bin/sh

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# Reset
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Black='\033[0;30m'        # Black
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victor-iyi

from typing import Generic
from typing import Iterable
from typing import TypeVar

# Generic type.
T = TypeVar('T')


class Vector(Generic[T]):
  """A light-weight Vector utility class, used to perform various operations

victor-iyi

"""
A program to determine if a number is a perfect number.
"""


def is_perfect_number(n):
    """Determines if a given number is a perfect number.

    Any number can be perfect number, if the sum of its
    positive divisors excluding the number itself is equal

victor-iyi

"""Improved estimation of how many lines of codes are in a project (using recursion)

   @author
     Victor I. Afolabi
     Director of AI, NioCraft, 115Garage.
     Email: javafolabi@gmail.com
     GitHub: https://github.com/victor-iyiola

   @project
     File: lines-of-code.py

victor-iyi

"""
  @author Victor I. Afolabi
  A.I. Engineer & Software developer
  javafolabi@gmail.com
  
  Created on 05 October, 2017 @ 03:35 PM.
  
  Copyright (c) 2017. Victor. All rights reserved.
"""

victor-iyi

# Shape = 2x3
a = [
        [1, 2, 3],
        [4, 5, 6]
    ]

# Shape = 2x3x2
b = [
        [[1, 1], [2, 2], [3, 3]],
        [[4, 4], [5, 5], [6, 6]]

victor-iyi

W0 = 2 * np.random.random(size=[input_dim, hidden_dim]) - 1
W1 = 2 * np.random.random(size=[hidden_dim, output_dim]) - 1

victor-iyi

W0 = 2 * np.random.random(size=[input_dim, hidden_dim]) - 1
W1 = 2 * np.random.random(size=[hidden_dim, output_dim]) - 1

victor-iyi

for i in range(10000):
    # Forward propagte our input to get a prediction
    l1 = sigmoid(np.dot(X, W0))
    l2 = sigmoid(np.dot(l1, W1))
    
    # Estimate how much we missed
    l2_error = (y - l2) ** 2
    l2_delta = l2_error * sigmoid(l2, prime=True)
    
    # Back propagate error in layer 2 into layer 1

victor-iyi

def sigmoid(Z, prime=False):
    if prime:
        return Z * (1 - Z)
    return 1 / (1 + np.exp(-Z))