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)

Python Any Where - Host, run, and code Python in the cloud

Basic plan gives you access to machines with a full Python environment already installed for free. You can develop and host your website or any other code directly from your browser without having to install software or manage your own server.

Python Any Where

Metaflow

Metaflow is a human-friendly Python library that helps scientists and engineers build and manage real-life data science projects. Metaflow was originally developed at Netflix to boost productivity of data scientists who work on a wide variety of projects from classical statistics to state-of-the-art deep learning.

pip install metaflow

Metaflow More Info

Metflow GitHub

Photon

Photon can extract the following data while crawling:

URLs (in-scope & out-of-scope)
URLs with parameters (example.com/gallery.php?id=2)
Intel (emails, social media accounts, amazon buckets etc.)
Files (pdf, png, xml etc.)
Secret keys (auth/API keys & hashes)
JavaScript files & Endpoints present in them
Strings matching custom regex pattern
Subdomains & DNS related data
The extracted information is saved in an organized manner or can be exported as json.

Python Regular Expression

A Regular Expression, is a sequence of characters that forms a search pattern. Python has a built-in package called re, which can be used to work with Regular Expressions.

(Example Code to remove symbols and numbers - compatible with Python 2.7.17)
import re
import string
input_str = "58597884|01:31:50|The rise of python stated by pythonforengineers blog"
print"Before Processing:",input_str
result = re.sub(r'\d+', '', input_str)
result = result.translate(string.maketrans("",""), string.punctuation)
print"After Processing:",result

More Details

Python Open Source Project - Manim

Manim is an animation engine for explanatory math videos. It's used to create precise animations programmatically. 

Install it from PyPI via pip:        pip3 install manimlib

Click here for more info

Surprise - A Python scikit for recommender systems

Surprise is a Python scikit building and analyzing recommender systems that deal with explicit rating data. Surprise stands for Simple Python Recommendation System Engine.

Surprise was designed with the following purposes in mind:

Give users perfect control over their experiments.
Alleviate the pain of dataset handling.
Provide various ready-to-use prediction algorithms.
Make it easy to implement new algorithm ideas.
Provide tools to evaluate, analyse and compare the algorithms performance.

For more info http://surpriselib.com

Performing Google Search using Python code

Install following two packages before executing the code below pip install beautifulsoup4 pip install google try: from googlesearch import search except ImportError: print("No module named 'google' found") # to search query = "python for engineers Blog" for j in search(query, tld="co.in", num=10, stop=1, pause=2): print(j)