Moobhi Review- Piku Emotion in Motion

Shoojit Sircar has written a love poem to the saga of probashi Bongalis, Kolkatta longing and the fine yet quixotic and sometimes insular Bong culture. He has relied on shortcuts and stereotypes to finish the story in the time alloted. Deepika looks great with Kajal laced Bengali Eyes, but someone needs to tell her to get accent training. Irrfan can act better with his eyes and mouth closed, than Karan Johar can act with his entire body.

Amitabh Bachchan just disappears into his role as Bhaskar Da. Moushmi Chatterjee lifts occasional sag into the story pace. What a nice story? If only non Bengalis knew more about their culture than just Bengali sweets.

piku-mos_650_103114032933

Dealing with zip files in R #rstats

> setwd("/home/ajay/Downloads")
> a=dir()
> class(a)
[1] "character"
> grep(".zip",a)
[1]  37  38  41  43  88  96 133
> b=grep(".zip",a)
> a[b]
[1] "alissa-coming-soon-v2-0(1).zip"            
[2] "alissa-coming-soon-v2-0.zip"               
[3] "CAX_EMC_Journalist_Data.zip"               
[4] "CAX_EMC_Racer_Data.zip"                    
[5] "matlab_R2015a_glnxa64.zip"                 
[6] "Photos.zip"                                
[7] "unvbasicvapp__9411003__vmx__en__sp0__1.zip"
> unzip("CAX_EMC_Racer_Data.zip")
> c=dir() 
library(Hmisc)

> c[c %nin% a] 
[1] "CAX_EMC_Racer_Garmin_Camera.csv" 
[2] "CAX_EMC_Racer_Garmin_Watch_Data.csv"
[3] "CAX_EMC_Racer_Motorcycle_Data.csv"
  ps- I know Hadley's convenient wrappR  packages are all the rage now, but nothing, i repeat
 nothing beats Frank Harell and Ripley's cool packages

	

DecisionStats Summer School in Delhi 2015 #rstats

This summer get a foothold in the world of data science. These are in classroom trainings for Delhi India and all prices are in INR only.

If you are interested apply here-

bit.ly/decisionstats

Screenshot from 2015-05-20 20:01:25

SUMMER SCHOOL 2015

  • Bring your own device. Hardware – with >2GB RAM and >20 GB Hard Disk Free
  • Eligibility Criterion – People Interested in a career as a data scientist. No prior skills are required but statistics and programming can help.
  • 1 class is of 2.5 hours followed by a break of 1 hour . Each Day has two classes per batch

Course Details

15 – 16 June 17- 18 June 19 June – 22 ,23,24 June 25 -26 June
Course Name Introduction to

Data Science

Introduction to Analytics

using Python

Introduction to

Analytics using R

SAS Language

Fundamentals

Hours 10 10 20 10
Classes 4 4 8 4
Days 2 2 4 2
Cost 8000
10000
12000
15000
25000

Taking all four courses gives you a saving of 80% with 50 hours total class time.

Instructor will teach in person and open for clearing doubts on the spot.

Course Outline

Basics of Data Science Introduction to Python Introduction to R Introduction to Interface
Basics of Analytics Introduction to iPython Introduction to R Studio Introduction to SAS language
LTV Analysis Introduction to Pandas Introduction to R Data Step
LTV Analysis Quiz Introduction to iPython Notebook Introduction to Rattle Proc Print
RFM Analysis IDE- IDLE and Spyder Deducer Proc Means and Proc Freq
RFM Analysis Quiz Python 1 Quiz R Quiz 1 SAS Quiz 1
Basic Stats Data Input Data Input Proc Univariate
Introduction to Modeling Data Analysis Data Analysis Do loops
Data Summarization Data Summarization Proc sgplot
Introduction to Google Analytics Data Visualization Data Visualization Proc SQL
Blogging Data Output Data Output SAS Macro Language
Web Analytics Quiz Ipython 2 Quiz R Quiz 2 menu driven options
data.table ODS Output
ggplot
sports analytics SAS Quiz 2
regression model
data mining
R Quiz 3
social network analysis
text mining
time series forecasting
Using apis
association analysis
R Quiz 4
RODBC
sqldf
spatial analytics
RMarkDown
Using Github
R Quiz 5

If you are interested apply here-

bit.ly/decisionstats