innat

Download FFmpeg for Windows

Steps

• Download FFmpeg
• Extract it and save it to C drive ( choose any location - it's optional )
• Set environment variable - copy the location of bin folder which is inside the extracted file and set the location on system path variable.
• Done!

innat

Supported Python versions

Python 2.7 is the only supported version in 2.x series. Python 3.x releases follow Numpy releases. For example Python 3.3 is no longer supported by Numpy so support for it has been dropped in opencv-python, too.

Currently, builds for following Python versions are provided:

• 2.7
• 3.4
• 3.5

innat

Problem Space

How to Include image or picture in jupyter notebook?

Method 1: Markdown Cell

Run like following on markdown cell,

![title]()

innat

Some GitHub Extensions that I use. They may also enable you to improve your productivity on GitHub.

1. Octotree allows easy exploration of the source code within the browser through a panel on the left.

2 github-dashboard provides the ability to filter events on the Github.com activity dashboard.

innat

Task

Set-up Raspberry Pi headlessly in Laptop, no HDMI no Monitor.

Necessary Software

• RASPBIAN STRETCH ISO file
• Etcher
• Advance IP scanner
• MobaXterm - By Choosing it
  • No Need PuTTY - exceptionally because already built-in.
• No Need VNC - already built-in.

innat

NumPy 1.7 (when np.pad was added) is pretty old now (it was released in 2013) so even though the question asked for a way without that function I thought it could be useful to know how that could be achieved using np.pad.

It's actually pretty simple:

>>> import numpy as np
>>> a = np.array([[ 1.,  1.,  1.,  1.,  1.],
...               [ 1.,  1.,  1.,  1.,  1.],
...               [ 1.,  1.,  1.,  1.,  1.]])
>>> np.pad(a, [(0, 1), (0, 1)], mode='constant')

array([[ 1., 1., 1., 1., 1., 0.],

innat

We can delete a key from a Python dictionary by the some following approaches.

Using the del keyword; it's almost the same approach like you did though -

     myDict = {'one': 100, 'two': 200, 'three': 300 }
     print(myDict)  # {'one': 100, 'two': 200, 'three': 300}
     if myDict.get('one') : del myDict['one']
     print(myDict)  # {'two': 200, 'three': 300}

innat

For left alignment

 <img align="left" width="600" height="200" src="https://www.python.org/python-.png">

For right alignment

<img align="right" width="600" height="200" src="https://www.python.org/python-.png">

And for center alignment

innat

map and filter function in python is pretty different because they perform very differently. Let's have a quick example to differentiate them.

map function

Let's define a function which will take a string argument and check whether it presents in vowel letter sequences.

def lit(word):
    return word in 'aeiou'

Now let's create a map function for this and pass some random string.

innat

Briefly:

np.dot is the dot product of two matrices.

|A B| . |E F| = |A*E+B*G A*F+B*H|
|C D|   |G H|   |C*E+D*G C*F+D*H|

Whereas np.multiply does an element-wise multiplication of two matrices.