Below are the solutions to these exercises on data transformation. ## Warning: package ‘tensorflow’ was built under R version 3.3.3 #################### # # # Exercise 1 # # # #################### sess = tf$Session() print(sess$run(a)) ## [,1] [,2] ## [1,] 3 12 sess$close() #OR with(tf$Session() %as% sess, { print(sess$run(a)) }) ## [,1] [,2] ## [1,] 3 […]

## Tensorflow – Basics Part 1: Exercises

Tensorflow is an open source, software library for numerical computation using data flow graphs. Nodes in the graph are called ops (short for operations), while the graph edges represent the R multidimensional data arrays (tensors) communicated between them. An op takes zero or more Tensors, performs some computation, and produces zero or more Tensors. In […]

## Tensorflow – Basics Part 1

Overview In this tutorial, we will go through the basics of Tensorflow. By the end of this series, you will have the background in order to use Tensorflow for deep learning models. Tensorflow is an open source software library for numerical computation using data flow graphs. Nodes in the graph are called ops (short for […]

## Data wrangling : Cleansing – Date

Data wrangling is the process of importing, cleaning, and transforming raw data into actionable information for analysis. It is a time-consuming process that is estimated to take about 60-80% of analysts’ time. In this series, we will go through this process. It will be a brief series with the goal of crafting the reader’s skills […]

## Data wrangling : Cleansing – Date Solutions

Below are the solutions to these exercises on data cleansing. #################### # # # Exercise 1 # # # #################### date <- as.Date(date_sep, format = "%d-%m-%Y") #OR date <- dmy(date_sep) #################### # # # Exercise 2 # # # #################### year(date) ## [1] 2017 2017 2017 #################### # # # Exercise 3 # # # […]

## Data wrangling : Cleansing – Regular expressions (3/3) Solutions

Below are the solutions to these exercises on data cleansing. ## Error in contrib.url(repos, type): trying to use CRAN without setting a mirror #################### # # # Exercise 1 # # # #################### grep("Merc", rownames(mtcars), value = TRUE) ## [1] "Merc 240D" "Merc 230" "Merc 280" "Merc 280C" "Merc 450SE" ## [6] "Merc 450SL" "Merc […]

## Data wrangling : Cleansing – Regular expressions (3/3)

Data wrangling is the process of importing, cleaning, and transforming raw data into actionable information for analysis. It is a time-consuming process that is estimated to take about 60-80% of analysts’ time. In this series, we will go through this process. It will be a brief series with the goal of crafting the reader’s skills […]

## Data wrangling : Cleansing – Regular expressions (2/3) Solutions

Below are the solutions to these exercises on data cleansing. #################### # # # Exercise 1 # # # #################### grep(pattern = ‘[3-6]’, bio, value = TRUE) ## [1] "24 year old" "R version 3.4.0 (2017-04-21)" #################### # # # Exercise 2 # # # #################### grep(pattern = ‘[Ay]’, bio, value = TRUE) ## [1] […]

## Data wrangling : Cleansing – Regular expressions (2/3)

Data wrangling, is the process of importing, cleaning and transforming raw data into actionable information for analysis. It is a time-consuming process which is estimated to take about 60-80% of analyst’s time. In this series we will go through this process. It will be a brief series with goal to craft the reader’s skills on […]

## Data wrangling : Cleansing – Regular expressions (1/3) Solutions

Below are the solutions to these exercises on data cleansing. #################### # # # Exercise 1 # # # #################### text <- sub(pattern = "\\.", "\\!", textmeta); text ## [1] "R|is|cool,|so|are|you|that|you|are|for|__|your|skills|by|solving|this|exercise! Moreover parenthesis symbol is []! Finally once you are done with this set go for a coffee, you deserve it!" #################### # # # […]