Great Way to learn Git easily

a great way to learn Git easily is here https://try.github.io/

Screenshot 2014-06-24 19.23.59

This is a much better designed code school project than the one for R

http://tryr.codeschool.com/

However Swirl is a great way to learn  R in an interactive way. its only drawback is it needs to be integrated with something like http://www.r-fiddle.org/#/ for a true automated browser only version

Why do I favor automated elearning solutions now? Because teaching the same thing again and again can be boring for the teacher and videos can be boring for the students. Note how the potential student is given positive reinforcement to boost his morale, something any good teacher know.

Price of Analytics Education from Indian Service Providers

This is an unedited list of education providers from India, with both classroom and online trainings. 1$ =55Rs. The list will be updated as and when changes occur or when a reader suggests. I will only be putting prices that can be referenced via a URL. Also later I will try and create an index to track prices. Because I have had relationships with a lot of people in Indian Analytics- I will try and put this in a Google Docs spreadsheet.

The basic template will  be

  • Service Provider-
  • Location-.
  • Type -Online /Classroom
  • URL (reference)
  • Dated-
  • Screenshot-

Example

  • Service Provider-Venturesity
  • Location-Bangalore
  • Type -Classroom
  • URL (reference) -http://www.venturesity.com/course/big-data-analytics-bootcamp/
  • Dated-11 June 2014
  • Screenshot-Screenshot 2014-06-11 12.23.59

 

How to share your iPython (or iJulia code)

Basically

 

1) Download as Ipython file from the File Option

Screenshot 2014-05-06 22.02.54

 

2) Use notepad to open the file downloaded. Copy the text contents

Screenshot 2014-05-06 22.06.03

3) Create a new gist at by pasting the text from step 2 here

https://gist.github.com/ (assumes you have a github account)

Screenshot 2014-05-06 22.06.43

 

4) Paste the url of the Gist into http://nbviewer.ipython.org/ to get your iNotebook url for sharing

5) To update your notebook, simply copy and paste the new IPython code by editing the gist again

 

6)

(example here- http://nbviewer.ipython.org/gist/decisionstats/62c5387624a9ba9015a4)

 

Screenshot 2014-05-06 22.08.22

Beginner’s Notes in JULIA Language

  • Packages
  1. Pkg.add(“RDatasets ”)  installs package RDatasets
  2. using  RDatasets –loads package RDatasets
  3. Pkg.update() Updates all packages

 

some packages to install IJulia, RDatasets, PyCall,PyPlot,Gadfly,Rif

  • Data Input -pwd() – Gets you the current working directory
  1. cd(“C:/Path”) -Sets the working directory to the new path , here C:/Path
  2. readdir() – Lists all the files present in the current working directory
  3. using DataFrames

a=readtable(“1.csv”)

or df=readtable(“adult.data.txt”,header=false)

or

df= collect(readdlm(“adult.csv”))

or from package

Using RDatasets

iris=dataset(“datasets”,”iris”)

  • Object Inspection
  1. summary(a) Gives the structure of object named  including class, dimensions,
  2. colnames(a) Gives the names of variables of the object
  3. typeof(a) Gives the class of a object like data.frame, list,matrix, vector etc

size(a) Givesthe dimension of object (rows column)

Plots

using Gadfly

plot(df,x=”x1″ ,color=”x15″,Geom.histogram)

plot(iris,x=”SepalLength”,y=”SepalWidth”,color=”Species”)

using PyPlot

boxplot(df[:x15])

Note- we can use df[:x15] notation to refer to x15 variable in Data Frame df

For missing values we use Data Arrays and @data to convert object to Data Array

Then use removeNA ( or dropna in Julia 0.3) to remove missing values so as to run functions like mean etc

The describe function gives the numerical summary

describe(df[:x1])
Min      17.0
1st Qu.  28.0
Median   37.0
Mean     38.58164675532078
3rd Qu.  48.0
Max      90.0
NAs      0
NA%      0.0%

 

NOTES-

1) Doesnt work very well on Win 32

2) Two interfaces – command line or IJulia Notebook

3) If you type an object name , gives you the first twenty and last twenty rows- which is quite intuitive designed.

4) PyCall is an interface to Python and Rif is an interface to R- but I had issues trying to work with Rif

5) Basically even simple things( functions!) are renamed in Julia- the effort seems to keep it distinct with R

6) PyPlot for basic plots and Gadfly for ggplot2 plots

 

Note- some of it was shown here-Updated

http://nbviewer.ipython.org/gist/decisionstats/62c5387624a9ba9015a4

Talking on Analytics

I will be talking to doctoral and MBA students at IIT Delhi on May 10. The talk is Data Analytics and Cloud Computing and will be there for 2 hours, but will be much more broad ranging than that including touching on HR Analytics and Data Science. If you are local to Delhi around this date- you can contact me in case you want to attend in person.

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IMG_0138

AN INTRODUCTION TO BIG DATA ANALYTICS AND CLOUD COMPUTING
In this talk we will discuss big data analytics including Hadoop and R, and the emergence of Cloud Computing. The focus will be on introducing fast changing technologies and what it means for enterprises and researchers.  We will also cover data science as potential career paths.

 

 

 


About-
Ajay Ohri is the founder of Decisionstats.com and author of R for Business Analytics. You can connect with him on http://linkedIn.com/in/ajayohri

 

Earlier Talks –

https://decisionstats.com/2014/04/20/talking-on-analytics-rstats-analytics-bigdata-sas-conferences/