Serverless Architecture

In simple words Serverless Architecture or Serverless computing is where developer doesn't need to worry about managing a server, server management and capacity planning decisions are completely hidden from developer.

what is Serverless Architecture ?

How to enable inbuilt Linux subsytem in Windows 10

Windows 10 provide inbuilt Linux subsystem , lets see how to enable it in your System.

Step 1 :   Go to Windows update and change uses mode to Developer Mode

select developer Mode in Windows update

How to check Palindrome

Check if a string is palindrome or not is one of most common question we encountered during our basic days.

Let's Solve this problem with a Naive but efficient approach in this case.

Pseudocode :

1. i=0, j=n
2. while i < j:
3.    check if i'th element is not equal to j'th
4.      then return False 
5.   else i++,j--
6. loop end
7. return True

When to use our own copy constructor while compiler already provides it

Actually compiler provided copy constructor copies all the values of members. So we are using a dynamic allocated member then only address of that member is copied in new object's member. It does not allocate new memory.

1. #include <iostream>
2. #include<cstring>
3. #include<cstdio>
4. using namespace std;
5. class XYZ
6. {
7.     public:
8.     char *p;
9.     XYZ(char *name,int l){
10.         p=new char[l+1];
11.         strcpy(p,name);
12.        
13.     }
14. };
16. int main() {
17.     XYZ obj1("str",3);
18.     printf("content of obj1.p is : %u\n",obj1.p);
19.     XYZ obj2=obj1;
20.     printf("content of obj2.p is : %u",obj2.p);
21. }

So here content of member p of obj1 and obj2 is same which is base address of string str

Note that memory is allocated once and pointer to that memory is set for both objects. So default copy constructor only copying members value that is value of obj1.p ( which is address of string "str" ) is copied to obj2.p

Private Constructor Function and Singleton Pattern

In C++ a constructor can be made private. But what is the use of private constructor ?

Think that you want to create a class in such a way that only one object can be created for this class something called Singleton pattern in C++.

Below is the program to do this.

1. #include<bits/stdc++.h>
2. using namespace std;
3. class ABC
4. {
5.    public:
6.    int t;
7.    static ABC creator()
8.    {
9.        static ABC x;
10.        return x;
11.     }
12.     private :
13.     ABC(){ t=10;}
14. };
15. int main()
16. {
17.     ABC obj1=ABC::creator();
18.     cout<<" Value of t= "<<obj1.t;
19.     //ABC obj2=ABC::creator()           returns same object
20. }

How it works?

Static function are class variable not object's so static function 'creator()' called using class_name::function_name.

Static object is created inside static function. So private constructor function is called which is a valid call since it is from inside of a member function. So obj1 is created and returned.

Next time when we call static function it does not create new object since object is declare as static so same will be returned.

So only one object is created

Best way to download file in Mint/Ubuntu ..

Linux (Debian/Mint/Ubuntu) provide really very powerful tools for lots of things. Download is a common thing that we use in daily life.
Linux provide a very powerful command line tool  that really enhance our download experience.
It is very powerful and very convenient.  Introducing to you "wget" commond.

Quick Dive to data handeling and machine learning in Python

This model show a quick way to apply different classification machine learning algorithm on data strored in CSV formate.

Python provide very powerful tools like pandas, numpy, and sklearn. we exploit them a lot.

 Source Identification using 2 Class of image¶

In [72]:

from sklearn.svm import SVC
from sklearn.tree import DecisionTreeClassifier
from sklearn.metrics import accuracy_score
from sklearn.preprocessing import normalize
import numpy as np
import pandas as pd
# matplotlib.pyplot as plt

Understanding Data¶

In [2]:

sony=pd.read_csv("Sony_NONIQM.csv")
sony.head()

73

In [3]:

nikon=pd.read_csv("Nikons_NONIQM.csv")
nikon.head()

Out[3]:

Easiest way to create android supported hotspot in Linuxmint/Ubuntu/debian

This approach doesn't require any additional tools. You can easily create access point that can be use by any mobile devices.

Just fallow these simple steps:

1. menu>preferences>network connections
   

Quick Python Pandas Basics

Lets Learn Pandas

In [1]:

import pandas as pd

Pandas series

pandas series is similar to numpy array, But it support lots of extra functionality like Pandaseries.describe()
Basic access is similar to numpy array, it support access by index( s[5] ) or slicing ( s[5:10] ).
It also support vectorise operation and looping like numpy array.
Implemented in C so it works very fast.

Note : Get Code for offline testing  Github_Link or nbviewer.jupyter link

Learn Basic of Numpy

Benfits of Pandas series¶

In [8]:

s=pd.Series([2,3,4,5,6])
print s.describe()

count    5.000000
mean     4.000000
std      1.581139
min      2.000000
25%      3.000000
50%      4.000000
75%      5.000000
max      6.000000
dtype: float64

Basics of Numpy & Pandas

Numpy and pandas are very popular packages used for data analysis. this post provide you quick guide to learn the basics of these. We assume you are familiar with vector operation . 

Numpy is mostly written in C & pandas are written over numpy & also uses C programming language as core implementation So these two are fast as compare to general data structure provided with python.

Numpy array is similar to python list but it contain all data of same data-type & it is much faster.

we can also treat numpy array as a vector.

Pandas uses scalar instead of list or numpy array but we can also visualize it as numpy array with some advance functionalities. 

Example

Numpy uses array whereas pandas used scaler

In [2]:

import numpy as np

Array are similar to python list , but it all element must be of same data type, and it faster than list¶

In [13]:

num = np.array([3,4,2,5,7,23,56,23,7,23,89,43,676,43])
num

Out[13]:

array([  3,   4,   2,   5,   7,  23,  56,  23,   7,  23,  89,  43, 676,  43])

Lets see some of functionality¶

Importing CSV File in Python

CSV file is one of most common used format we encounter. Let see few technique to efficiently import these data to python for better & efficient use.
CSV is also known as comma separated format. you can easily write a code to import CSV data .
But today we will see some of very efficient way to do so.

Python provide few package like CSV, unicodecsv, pandas Thease packages help you to do your job.

• CSV : package follow basic approach & slow , it reads data line by line & split.
• unicodecsv : Import data & create a list of dictionaries each data is associated with its attribute as key. So it  coud be very usefull in many cases but this process is also slow
• pandas : This technique is very fast as compare to  above two methods.

You can download & test in your computer using Ipython notebook [Github_link]

Example

In [2]:

import unicodecsv
import pprint
import csv

In [3]:

csv_file_name="enrollments.csv"

Json Import of csv file¶

Import data in json formate, All data are imported as string¶

In [16]:

enrolment = []

f=open(csv_file_name,'rb')

reader =unicodecsv.DictReader(f)
#reader is a itterater so loop is possible only once
print "type(reader) =",reader

#for each_row in reader:
#    enrolment.append(each_row)
enrolment=list(reader) #shorthand for above two line

#close file
f.close()

print "Total no of row : ",len(enrolment),"\n\n"

#print demo data
pprint.pprint(enrolment[1])

type(reader) = <unicodecsv.py2.DictReader instance at 0x04A10A08>
Total no of row :  1640 


{u'account_key': u'448',
 u'cancel_date': u'2014-11-10',
 u'days_to_cancel': u'5',
 u'is_canceled': u'True',
 u'is_udacity': u'True',
 u'join_date': u'2014-11-05',
 u'status': u'canceled'}

## Simple import

Pattern Search using Regular Expression in Python

In our daily life we found lots of problem of pattern search. like find all mobile numbers, or emails etc  from  given web page or from any file.

Writing manual code for that is not efficient and also very messy. Regular Expression is very popular technique used for pattern search (All compiler & interpreter use it ) & it is very easy to implement & it is very efficient .

I suggest you to write a code for extracting all emails from a webpage without using regular expression & test it .
Emails found on a webpage may follow some of these pattern like

abc_7@gmail.com	abcd(at)hotmail.in
abcd@@stanford.edu.org	abcd@mnp(dot)com

Pong Game In python

This is very easy if you are intermediate in python and good in basic physics and basic maths.
You need to know basics of reflection, velocity, acceleration, and basics mathematics in order to calculate collision .When boundary of pong just touches wall or paddle are situation of collision. rest of thing is just basic python.

We need to increase velocity of pong with time so we add some constant small  acceleration that is being triggered after some small time interval . why small because if we use large acceleration or time then change in velocity will be sudden, so speed of pong increase suddenly.

Using SVM Classifier

Support vector Machine (SVM) is one of most famous machine learning tool for classification problem. This is supervised learning technique .Read More

SVM Margin

 we are going to see how to use SVM classifier in python.

Our Demonstration uses digit dataset . This dataset uses 64 feature vector to identify handwritten digit [0, 1, 2, 3, 4, 5, 6, 7, 8, 9] . It means this 64 feature extracted from Handwritten digit used to classify handwritten digit in 9 classes .

So Again we gonna use skilearn Python Package .

Using Naive Bayes classifier

This is most basic classifier, It uses concept of probability in order to predict the class of input feature data . Read More

We gonna see how to use Naive Bayes Classifier very easily using python.

Bayes rule

Prerequisite:

• Python 2
• sklearn [Python Module]
• Numpy  [Python Module]

We are going to apply this algorithm on Iris dataset .

Python In Sort

Python is one of most famous Programming Language. This is summary of python programming language for Quick Start to Python Programming .

{ Zoom or download picture}

Easieast Way to create Access Point Hotspot in Ubuntu 15.04

Creating Hotspot in Ubuntu is easier task . But many people (beginners) find hard to cerate hotspot access point to connect other devices like Android phone,tablets etc.

So , I gonna so you A graphical way To do it very easily.

1. Download kde-nm-connection-editor (Plasma-nm) from Ubuntu Software center. kde-nm-connection-editor. (you may not directly find it in software search so follow link given, or you may search and install plasma-nm)

   

   kde-nm-connection-editor link
   
   

Setup DropBox In Ubuntu

Dropbox is one of most famous cloud storage service. So we gonna setup dropbox in Ubuntu System.

1. Go to Ubuntu software Center > Search for Dropbox and Install

   

   Dropbox Ubuntu Software center
   
   

Array Aptitude

Divide array in two part such that sum of array left to partition index i  is equal to sum of array right to partition index i.

That is A[0]+A[1]...+A[i-1]=A[i+1]+....+A[n]

This is slightly tricky question but very easy to solve and code ,if you find the trick.

Algorithm:

• Find the cumulative sum at each index of array
• loop through array and check  A[i-1]==A[n]-A[i] , If condition Satisfy for any index i, means array can be partition in two group with this condition,So print "YES" else "NO"
• Use special case if array has only 1 element then print YES
• if array has only two element then print "NO"

Finding First and Last occurrence in sorted list

Finding first and last occurrence of given number in sorted list is a very easy problem and can easily solved by leaner search with worse case Time complexity O(n) .
But We can Achieve faster search of first and last occurrence of a number by exploiting sorted feature of list.
We can  search  occurrence of any number in sorted list in O(log(n)) Time Complexity by using Binary search Algorithm.