Skip to main content

Angular vs React

An attempt to answer one question which all people trying to pick a front end framework has . Is Angular or React the right choice ? Angular vs React is a burning adoption question on most Project planning sessions and one which often a developer has to confront. React is a Facebook supported initiative and is a javascript library . It would be wrong to call it a framework based on its initial release versions . It helps to create resusable components in applications and is javascript based . Angular has equally competent heritage from Google .With Angular being a new version to previous Angular JS which was widely successful. Angular has now ditched Javascript and adopted Typescript , i was very skeptic of this choice especially typescript being previously unknown in the front end developer circles . Once I started using Typescript I could see some clear advantages  and choice for strong typing  which was missing in Javascript for long was being enforced. Of course I

Picking a data set and trying to solve the problem.

Problem for us :

Using Machine learning we will try to predict which valuable employees will leave next. And also create data explorations based on the dataset in hand.At large the application will be developed using R shiny and R for data analysis and presentation.
At the data exploration phase, we are also considering using Python along with R so as to understand the differences in the platforms.

Problem description :
We intend to consider the HR survey results and understand why employees are leaving prematurely?
Fields in the dataset include:
·         Satisfaction Level
·         Last evaluation
·         Number of projects
·         Average monthly hours
·         Time spent at the company
·         Whether they have had a work accident
·         Whether they have had a promotion in the last 5 years
·         Departments (column sales)
·         Salary
·         Whether the employee has left

Dataset Links
The data is from Kaggle  

Technologies and Tools

Technologies: - R, R Shiny
Tools: - R Studio

There are many steps involved in creating a machine learning prediction model
Machine Learning Workflows are :-
  • Asking the right question
  • Preparing data
  • Selecting the algorithm
  • Training the model
  • Testing the model                                                                                                                          Once you have prepared your data and chosen an algorithm to train the dataset then you should test the model .After wards we created a R shiny based Webapp to expose an interface for the HR to upload the survey results and then get a prediction output on the top 300 employees likely to leave .You can find the code here
Instructions 

Run the selecting Algorithm.rmd file to understand the data and why we selected logical regression algorithm
Now install R studio and the necessary libraries listed here

Now run the Server.R file in R studio to get the application deployed .Upload the testing.csv survey results and the application will display the predicted results of the first 300 employees most likely to leave.

You may find the code here

https://github.com/Sreekumar4567/machineLearningCA.git

Comments

Popular posts from this blog

Scrumban using Asana

I had to create a project management practice in Agile for one of my projects. I had experience in working with Scrum  and Scrumban Agile methodolgies . I decided to adopt Scrumban as i found it better that Scrum and more suited for product development with uncertain requirements and often user stories which require a depeer research and understanding . You can read on further from the links below on Scrumban https://www.agilealliance.org/what-is-scrumban/ http://leansoftwareengineering.com/ksse/scrum-ban/ I had to choose a tool that was open source and readily available , I evaluated the below tools Taiga  Trello Asana Of the above I found Asana highly suitable and configurable and bingo they also had a mobile application which was quite user friendly. The  Sprints were planned for 2 weeks duration and a Milestone of 1 month duration . Each Milestone had two Sprints . For scrumban I choose the below project structure Here the Backlog had the backlog item

Angular vs React

An attempt to answer one question which all people trying to pick a front end framework has . Is Angular or React the right choice ? Angular vs React is a burning adoption question on most Project planning sessions and one which often a developer has to confront. React is a Facebook supported initiative and is a javascript library . It would be wrong to call it a framework based on its initial release versions . It helps to create resusable components in applications and is javascript based . Angular has equally competent heritage from Google .With Angular being a new version to previous Angular JS which was widely successful. Angular has now ditched Javascript and adopted Typescript , i was very skeptic of this choice especially typescript being previously unknown in the front end developer circles . Once I started using Typescript I could see some clear advantages  and choice for strong typing  which was missing in Javascript for long was being enforced. Of course I

For Machine learning should we use R or Python ?

Some real important differences to consider when you are choosing  R  or  Python  over one another: Machine Learning  has 2 phases. Model Building and Prediction phase. Typically, model building is performed as a batch process and  predictions are done realtime . The model building process is a compute intensive process while the prediction happens in a jiffy. Therefore, performance of an algorithm in Python or R doesn't really affect the turn-around time of the user. Python 1, R 1. Production:  The real difference between Python and R comes in being production ready. Python, as such is a full fledged programming language and many organisations use it in their production systems. R is a statistical programming software favoured by many academia and due to the rise in data science and availability of libraries and being open source, the industry has started using R. Many of these organisations have their production systems either in Java, C++, C#, Python etc. So, ideally they w