Showing posts with label github. Show all posts
Showing posts with label github. Show all posts

Friday, 29 September 2017

Letters and Symbols in MarkdDown

Thursday, 28 September 2017

Mathematics in Markdown


From Wiki - 
Markdown is a lightweight markup language with plain text formatting syntax designed so that it can be converted to HTML and many other formats using a tool by the same name.[8] Markdown is often used to format readme files, for writing messages in online discussion forums, and to create rich text using a plain text editor(extensions - *.markdown , *.md ). website
Best thing of markdown files is you can convert the same into html without any issue. 



I've introduced with Markdown files when I have started to put my code on GitHub (https://github.com/atulsingh0). Started with little up n downs but after I've fallen for it, Its easy to write ReadMe or Math Equations files in markdown with little help.

In this tutorial, I have focused on Mathematics part only, for writing math formulas, Markdown is using LaTeX symbols for Greek letters, Brackets, Sign operator and lots of other symbols.

I have consolidated few of them and will add more,
Hoping, you will find it useful -  Direct Link

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Saturday, 14 January 2017

Learning Numpy #2

Thursday, 12 January 2017

Learning Numpy #1


Numpy is a python library used for numerical calculations and this is better performant than pure python. In this notebook, I have shared some basics of Numpy and will share more in next few posts. I hope you find these useful.





Click Here for Next Tutorial ~

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Wednesday, 11 January 2017

My Learning Path for Machine Learning


I am a Python Lover guy so my way includes lots of Python points. If you dont know the basics of this wonderful language, start it from HERE else you can follow the links which I am going to share.

Learning ML is not only studying ML algorithms, it includes Basic Algebra, Statistics, Algorithms, Programming and lot more. But no need to afraid as such :-) we need to start from somewhere.....

This is my github repo, you can fork it and follow me with these 2 links --

Fork Fork
Follow - Follow @atulsingh0
I am still updating this list and welcome you to update this as well.



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Friday, 6 January 2017

10 minutes with pandas library

Thursday, 5 January 2017

Learning Pandas #5 - read & write data from file

Wednesday, 4 January 2017

Learning Pandas #4 - Hierarchical Indexing

Sunday, 1 January 2017

Learning Pandas #3 - Working on Summary & MissingData

Saturday, 31 December 2016

Learning Pandas - DataFrame #2

Friday, 30 December 2016

Learning Pandas - Series #1

Wednesday, 28 December 2016

Learning Graphlab - SFrame #2

In last post Learning Graphlab - SFrame #1, we have learn basics of SFrame, like how to create, add or delete the columns in SFrame. In this post, we will revise it once again and learn some advance features of SFrame. Have a good learnng !!!

You can view the Jupyter Notebook for the same HERE




Wednesday, 30 November 2016

Learning Graphlab - SFrame #1


Hoping you guys went through the last post (Lnk -> Getting Started with Graphlab), In this post we will do some handson SFrame datatype of Graphlab which is same as dataframe of pandas python library.

i. Reading the CSV file
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rdCSV

ii. save DataSet 
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iii. load DataSet
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iv. Check Total Rows and Columns
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rowNum

v. Check Columns data type and Name
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colTypes

vi. Add new column
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addCol

vii. Delete column
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viii. Rename column
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renameCol

ix. Column Swapping (location)
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Wednesday, 12 October 2016

Script to Auto Compress the System Log Files


This Script is originally written by "Andy Welter" to compress the linux system log files. I have modified it to work better. You can find it below (modified version) -

Script Usage:
logroll [-compress|-nocompress]

$ logroll -compress
# compress the log files and move to archive directory

logroll -nocompress
# Move the file to archive directory with compressing it 


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Tuesday, 31 May 2016

Python Points #13 - Comprehensions

Friday, 11 March 2016

Python Points #12 - execute OS commads

Thursday, 10 March 2016

Python Points #11 - Set