Explore well versed other functions, flatten operator and other available options to pass parameters
Let me know if anything is required. Happy to help.
Ping me google #bobrupakroy.
Talk soon!
Get to know the implementation of apache Pig relational operators like order, limit, distinct, groupby.
Let me know if anything is required. Happy to help.
Ping me google #bobrupakroy.
Talk soon!
Enhance analysis with detailed examples of Relational Operators - II includes Foreash, Filter, Join, Co-Group, Union and much more.
Let me know if anything is required. Happy to help.
Ping me google #bobrupakroy.
Talk soon!
Conduct ways to impute missing values for categorical, factor, and continuous variables. Let me know if anything is required ping me at google #bobrupakroy
Impute missing values for categorical and continuous variables in ways using R Studio and R programming. If you wish to try the same using python check out my other articles or ping me @ google #bobrupakroy
Meet Ramda, a functional programming helper library which can replace Lodash and Underscore in various use-cases. Ramda is all curried and adds various facilities for increasing code reuse.
Get to know the implementation of apache Pig relational operators like order, limit, distinct, groupby.
Let me know if anything is required. Happy to help.
Ping me google #bobrupakroy.
Talk soon!
Enhance analysis with detailed examples of Relational Operators - II includes Foreash, Filter, Join, Co-Group, Union and much more.
Let me know if anything is required. Happy to help.
Ping me google #bobrupakroy.
Talk soon!
Conduct ways to impute missing values for categorical, factor, and continuous variables. Let me know if anything is required ping me at google #bobrupakroy
Impute missing values for categorical and continuous variables in ways using R Studio and R programming. If you wish to try the same using python check out my other articles or ping me @ google #bobrupakroy
Meet Ramda, a functional programming helper library which can replace Lodash and Underscore in various use-cases. Ramda is all curried and adds various facilities for increasing code reuse.
There's a revolution calling! Lambda expressions are coming in Java 8 but how can developers benefit? We'll go through a series of code examples, that show how to:
Use the new lambda expressions feature
Write more readable and faster collections processing code using the Streams API
Build complex data processing systems with the new collector abstraction
Use lambda expressions in your own code
Functional Programming for OO Programmers (part 2)Calvin Cheng
Code examples demonstrating Functional Programming concepts, with JavaScript and Haskell.
Part 1 can be found here - http://www.slideshare.net/calvinchengx/functional-programming-part01
Source code can be found here - http://github.com/calvinchengx/learnhaskell
Let me know if you spot any errors! Thank you! :-)
This presentation educated you about R - Factors with example syntax and demo program of Factors in Data Frame, Changing the Order of Levels and Generating Factor Levels.
For more topics stay tuned with Learnbay.
METHODS DESCRIPTION
copy() They copy() method returns a shallow copy of the dictionary.
clear() The clear() method removes all items from the dictionary.
pop() Removes and returns an element from a dictionary having the given key.
popitem() Removes the arbitrary key-value pair from the dictionary and returns it as tuple.
get() It is a conventional method to access a value for a key.
dictionary_name.values() returns a list of all the values available in a given dictionary.
str() Produces a printable string representation of a dictionary.
update() Adds dictionary dict2’s key-values pairs to dict
setdefault() Set dict[key]=default if key is not already in dict
keys() Returns list of dictionary dict’s keys
items() Returns a list of dict’s (key, value) tuple pairs
has_key() Returns true if key in dictionary dict, false otherwise
fromkeys() Create a new dictionary with keys from seq and values set to value.
type() Returns the type of the passed variable.
cmp() Compares elements of both dict.
It covers- Introduction to R language, Creating, Exploring data with Various Data Structures e.g. Vector, Array, Matrices, and Factors. Using Methods with examples.
Learn to manipulate strings in R using the built in R functions. This tutorial is part of the Working With Data module of the R Programming Course offered by r-squared.
Analysis of data in Python with SciPy and pandas, Ubuntu installation, PyCharm configuration, Series, DataFrame, big data, medical data, merging data, groupby, graphing data, iPython using Wakari.io, and analyzing stock prices of US automakers including Ford and Telsa. As presented at Penguicon 2016.
There's a revolution calling! Lambda expressions are coming in Java 8 but how can developers benefit? We'll go through a series of code examples, that show how to:
Use the new lambda expressions feature
Write more readable and faster collections processing code using the Streams API
Build complex data processing systems with the new collector abstraction
Use lambda expressions in your own code
Functional Programming for OO Programmers (part 2)Calvin Cheng
Code examples demonstrating Functional Programming concepts, with JavaScript and Haskell.
Part 1 can be found here - http://www.slideshare.net/calvinchengx/functional-programming-part01
Source code can be found here - http://github.com/calvinchengx/learnhaskell
Let me know if you spot any errors! Thank you! :-)
This presentation educated you about R - Factors with example syntax and demo program of Factors in Data Frame, Changing the Order of Levels and Generating Factor Levels.
For more topics stay tuned with Learnbay.
METHODS DESCRIPTION
copy() They copy() method returns a shallow copy of the dictionary.
clear() The clear() method removes all items from the dictionary.
pop() Removes and returns an element from a dictionary having the given key.
popitem() Removes the arbitrary key-value pair from the dictionary and returns it as tuple.
get() It is a conventional method to access a value for a key.
dictionary_name.values() returns a list of all the values available in a given dictionary.
str() Produces a printable string representation of a dictionary.
update() Adds dictionary dict2’s key-values pairs to dict
setdefault() Set dict[key]=default if key is not already in dict
keys() Returns list of dictionary dict’s keys
items() Returns a list of dict’s (key, value) tuple pairs
has_key() Returns true if key in dictionary dict, false otherwise
fromkeys() Create a new dictionary with keys from seq and values set to value.
type() Returns the type of the passed variable.
cmp() Compares elements of both dict.
It covers- Introduction to R language, Creating, Exploring data with Various Data Structures e.g. Vector, Array, Matrices, and Factors. Using Methods with examples.
Learn to manipulate strings in R using the built in R functions. This tutorial is part of the Working With Data module of the R Programming Course offered by r-squared.
Analysis of data in Python with SciPy and pandas, Ubuntu installation, PyCharm configuration, Series, DataFrame, big data, medical data, merging data, groupby, graphing data, iPython using Wakari.io, and analyzing stock prices of US automakers including Ford and Telsa. As presented at Penguicon 2016.
Building and Incredible Machine with Pipelines and Generators in PHP (IPC Ber...dantleech
Did you know that Generators and Pipelines can be combined in order to
solve software engineering problems?
Generators have been available to us in PHP for about 5 years, they are a very
powerful tool in a developers toolbox, they can be used to make your life
easier (e.g. as data providers in PHPUnit), to help process large amounts of
data, and even to enable co-operative multi-tasking.
Pipelines provide a way to compose complex tasks from stages.
In this talk we will briefly discuss a specific problem in PHPBench (a
benchmarking tool for PHP) which can be solved through the use of Generators
(and pipelines!). We will then explore both topics generally, before combining
them into an Incredible Machine in a live coding session.
The GPars (Groovy Parallel Systems) project provides multiple abstractions for concurrent, parallel programming in Groovy and Java. Rather than dealing directly with threads, synchronization, and locks, or even the java.util.concurrent classes added in Java 5, the project allows you to think in terms of actors, data flows, or composable asynchronous functions (to name a few).
In this talk, I covered the basics of GPars, including what it's like to learn to use it. Although I've done a fair amount of concurrent programming, I've just started using GPars. As such, this talk should be suitable for Groovy beginners.
Introduction to Apache Pig.
Apache pig is a platform which provides to modes for analyzing datasets. One is local mode over local file system and other is over HDFS. Apache Pig consists of a high-level language called PigLatin which is a Query language.
Hierarchical Clustering - Text Mining/NLPRupak Roy
Documented Hierarchical clustering using Hclust for text mining, natural language processing.
Thanks, for your time, if you enjoyed this short article there are tons of topics in advanced analytics, data science, and machine learning available in my medium repo. https://medium.com/@bobrupakroy
Clustering K means and Hierarchical - NLPRupak Roy
Classify to cluster the natural language processing via K means, Hierarchical and more.
Thanks, for your time, if you enjoyed this short article there are tons of topics in advanced analytics, data science, and machine learning available in my medium repo. https://medium.com/@bobrupakroy
Network Analysis using 3D interactive plots along with their steps for implementation.
Thanks, for your time, if you enjoyed this short article there are tons of topics in advanced analytics, data science, and machine learning available in my medium repo. https://medium.com/@bobrupakroy
Explore detailed Topic Modeling via LDA Laten Dirichlet Allocation and their steps.
Thanks, for your time, if you enjoyed this short video there are tons of topics in advanced analytics, data science, and machine learning available in my medium repo. https://medium.com/@bobrupakroy
Widely accepted steps for sentiment analysis.
Thanks, for your time, if you enjoyed this short video there are tons of topics in advanced analytics, data science, and machine learning available in my medium repo. https://medium.com/@bobrupakroy
Process the sentiments of NLP with Naive Bayes Rule, Random Forest, Support Vector Machine, and much more.
Thanks, for your time, if you enjoyed this short slide there are tons of topics in advanced analytics, data science, and machine learning available in my medium repo. https://medium.com/@bobrupakroy
Detailed Pattern Search using regular expressions using grepl, grep, grepexpr and Replace with sub, gsub and much more.
Thanks, for your time, if you enjoyed this short slide there are tons of topics in advanced analytics, data science, and machine learning available in my medium repo. https://medium.com/@bobrupakroy
Detailed documented with the definition of text mining along with challenges, implementing modeling techniques, word cloud and much more.
Thanks, for your time, if you enjoyed this short video there are tons of topics in advanced analytics, data science, and machine learning available in my medium repo. https://medium.com/@bobrupakroy
Bundled with the documentation to the introduction of Apache Hbase to the configuration.
Let me know if anything is required. Happy to help.
Ping me google #bobrupakroy.
Understand and implement the terminology of why partitioning the table is important and the Hive Query Language (HQL)
Let me know if anything is required. Happy to help.
Ping me google #bobrupakroy.
Installing Apache Hive, internal and external table, import-export Rupak Roy
Perform Hive installation with internal and external table import-export and much more
Let me know if anything is required. Happy to help.
Ping me google #bobrupakroy.
Well illustrated with definitions of Apache Hive with its architecture workflows plus with the types of data available for Apache Hive
Let me know if anything is required. Happy to help.
Ping me google #bobrupakroy.
Automate the complete big data process from import to export data from HDFS to RDBMS like sql with apache sqoop
Let me know if anything is required. Happy to help.
Ping me google #bobrupakroy.
Apache Scoop - Import with Append mode and Last Modified mode Rupak Roy
Familiar with scoop advanced functions like import with append and last modified mode.
Let me know if anything is required. Happy to help.
Ping me google #bobrupakroy.
Get acquainted with the differences in scoop, the added advantages with hands-on implementation
Let me know if anything is required. Happy to help.
Ping me google #bobrupakroy.
Get acquainted with a distributed, reliable tool/service for collecting a large amount of streaming data to centralized storage with their architecture.
Let me know if anything is required. Happy to help.
Ping me google #bobrupakroy.
take care!
Get to know about casting of data from one to another type and reference field by position and much more
Let me know if anything is required. Happy to help.
Ping me google #bobrupakroy.
Talk soon!
Pig Latin, Data Model with Load and Store FunctionsRupak Roy
Documented with the two data types of PiG Data Model including Complex PIG data types in detail.
Let me know if anything is required. Happy to help.
Ping me google #bobrupakroy.
Talk soon!
Well-versed explanation of apache pig for analyzing the massive amount of data with its components pig latin, execution environments, and the high-level language pig architecture.
Let me know if anything is required. Happy to help.
Ping me google #bobrupakroy.
Talk soon!
Embracing GenAI - A Strategic ImperativePeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
Instructions for Submissions thorugh G- Classroom.pptxJheel Barad
This presentation provides a briefing on how to upload submissions and documents in Google Classroom. It was prepared as part of an orientation for new Sainik School in-service teacher trainees. As a training officer, my goal is to ensure that you are comfortable and proficient with this essential tool for managing assignments and fostering student engagement.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
Palestine last event orientationfvgnh .pptxRaedMohamed3
An EFL lesson about the current events in Palestine. It is intended to be for intermediate students who wish to increase their listening skills through a short lesson in power point.
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdfTechSoup
In this webinar you will learn how your organization can access TechSoup's wide variety of product discount and donation programs. From hardware to software, we'll give you a tour of the tools available to help your nonprofit with productivity, collaboration, financial management, donor tracking, security, and more.
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
Francesca Gottschalk - How can education support child empowerment.pptxEduSkills OECD
Francesca Gottschalk from the OECD’s Centre for Educational Research and Innovation presents at the Ask an Expert Webinar: How can education support child empowerment?
2. Other Functions
Average:
grunt> grouped = group dataTransaction by CustomerName
grunt> average = FOREACH grouped GENERATE group, AVG
( dataTransaction.TransAmt1);
COUNT: doesn’t count the NULL VALUES
grunt> cnt = foreach grouped generate group,
COUNT(dataTransaction);
grunt> dump cnt;
COUNT_STAR: counts even the NULL VALUES
grunt> cntStar = foreach grouped GENERATE group,
COUNT_STAR($1);
Rupak Roy
3. Concatenate:
grunt> c = foreach concat.csv GENERATE
CONCAT($0,$1);
Multiple concatenate:
grunt> c = foreach concat.csv GENERATE
CONCAT($0,’-’,Transaction_ID);
Is Empty: to check if a bag or map is empty
grunt> F = filter dataTransaction by IsEmpty($1);
Or
grunt> F = filter dataTransaction by Not IsEmpty($1);
Rupak Roy
4. MAX/MIN
grunt> g = group dataTransaction by
CustomerName;
grunt> m= foreach g generate group ,
MIN( dataTransaction.TransAmt1);
or
m = foreach g generate
dataTransaction.CustomerName,
MIN(dataTranscation.TransAmt1);
grunt> m= foreach g generate
dataTransaction.CustomerName,
MAX( dataTransaction.TransAmt1);
Rupak Roy
5. SIZE: is used to calculate the size of the data
according to the Pig data type
grunt> S =foreach dataTransaction generate
SIZE($0), SIZE(CustomerName),SIZE($2);
Rupak Roy
6. SUM
grunt> g = group dataTransaction by
CustomerName;
grunt> s= foreach grouped generate
dataTransaction.CustomerName,
SUM( dataTransation.TransAmt1)
Note: SUM, MAX/MIN, COUNT, COUNT_STAR,AVG
requires GROUP statement before we apply the
functions
Rupak Roy
7. Flatten Operator
It used to change the structure of the tuples and
bags. Flatten un-nest tuples and bags.
For example: consider the tuple has structure like
(a(b,c)). If we add FLATTEN such as GENERATE
flatten($0) it will cause the Tuple to become
(a,b,c)
Again, if we have tuple in the from of
(a,{(b,c,),(d,e)}) which is a group generated by
GROUP OPERATOR and add GENERATE FLATTEN
$0 will give you (a,b,c) and (a,d,e)
Rupak Roy
8. Run Pig Scripts directly from a file
First create a file and save it in a .pig extension.
Type vi output.pig in the terminal
Then write the Pig script
A= LOAD ‘home/hduser/datasets/store.csv’ using
PigStorage(‘,’) as ( )
B= foreach A generate $0,$2;
Now, save the file as output.pig ( or with any .pig extension)
and now execute from any terminal
[bob$localhost~]$ pig –x local /home/hduser/output.pig
Note: if you want to use in HDFS just type only ‘ pig’
And for local mode ‘ pig –x local ‘
Rupak Roy
9. Pig gives you 2 available options to
pass parameters:
1. Using file: -param_file path to the
parameter file.
2. Using command line: -p,-param key value
pair of the form param=val
Rupak Roy
10. Passing Parameters
USING COMMAND LINE:
Create a new file:
vi output1.pig
A= LOAD ‘home/hduser/datasets/store.csv’ using PigStorage(‘,’) as
( )
B = FILTER A by Place ==’$Place’;
DUMP B;
Save the file as output1.pig or with any name and execute the file from
terminal.
[bob$localhost~]$ pig -x local -p Place=‘Alberta’ output1.pig
To pass multiple parameters:
pig -x local -p Place=‘Alberta’ -p Age=‘29’ -p Product=‘electronics’
output1.pig
Rupak Roy
11. USING FILE:
Create a Parameter file using: vi pfile type i to enter
insert mode
Then type CustomerName == ‘Carl Jackson’
threshold = 5
To exit from insert mode Press Esc
then type :wq! To save the contents
Pig –param_file pfile home/hduser/displayoutput.pig
Rupak Roy
12. Next
Flume, a distributed, reliable tool for
collecting large amount of streaming
data.
Rupak Roy