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Public Datasets for Research & Innovation on Coronavirus

Python Programming for Quantitative Economics

This website presents a set of lectures on python programming for quantitative economics, designed and written by Thomas J. Sargent and John Stachurski.

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A python program for neural network trained with backpropagation with sigmoid function

import numpy as np
def nonlin(x,deriv=False):
    if(deriv==True):
        return x*(1-x)
    return 1/(1+np.exp(-x))
X = np.array([  [0,0,1],
                [0,1,1],
                [1,0,1],
                [1,1,1] ])
y = np.array([[0,0,1,1]]).T
np.random.seed(1)
syn0 = 2*np.random.random((3,1)) - 1
for iter in range(10000):
    l0 = X
    l1 = nonlin(np.dot(l0,syn0))
    l1_error = y - l1
    l1_delta = l1_error * nonlin(l1,True)
    syn0 += np.dot(l0.T,l1_delta)
print ("Output After Training:")
print (l1)

Pong - Python Game Tutorial

A Pong clone game tutorial for beginners using Python 3

First Come First Serve Process scheduling using python

process = []
total_waiting_time = 0
n = int(raw_input('Enter the total no of processes: '))
for i in xrange(n):
process.append([])
process[i].append(raw_input('Enter process name: '))
process[i].append(int(raw_input('Enter process arrival time : ')))
total_waiting_time += process[i][1]
process[i].append(int(raw_input('Enter process burst time: ')))
print ''

process.sort(key = lambda process:process[1])

print 'Process Name\tArrival Time\tBurst Time'
for i in xrange(n):
print process[i][0],'\t\t',process[i][1],'\t\t',process[i][2]

print 'Total waiting time: ', total_waiting_time
print 'Average waiting time: ',(total_waiting_time/n)

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Public Datasets for Research & Innovation on Coronavirus

Python Programming for Quantitative Economics

A python program for neural network trained with backpropagation with sigmoid function

Pong - Python Game Tutorial

First Come First Serve Process scheduling using python