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Md Rana Mahmud
Dhaka, Bangladesh
Data Scientist, Statistician, Programmer and React Developer with 4 years experience.
CodersRank Score
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This represents your current experience. It calculates by analyzing your connected repositories. By measuring your skills by your code, we are creating the ranking, so you can know how good are you comparing to another developers and what you have to improve to be better
Information on how to increase score and ranking details you can find in this blog post.
748
CodersRank Rank
Top 1%
Based on:
7 eventsTop 50
HTML
Developer
Bangladesh
Top 5
Jupyter Notebook
Developer
Bangladesh
Top 50
Python
Developer
Bangladesh
Highest experience points: 0 points,
0 activities in the last year
Jupyter Notebook
109.2
exp.
Python
68.5
exp.
HTML
117.6
exp.
Java
39.1
exp.
JavaScript
103.8
exp.
CSS
66.7
exp.
C++
13.5
exp.
JSON
112.6
exp.
Batchfile
14
exp.
SCSS
14.4
exp.
Swift
9.1
exp.
TypeScript
26.9
exp.
Objective-C
10.6
exp.
List your work history, including any contracts or internships
SHAFI CONSULTANCY LIMITED
Mar 2018 - Sep 2018 (6 months)
Statistical Programmer
* Build prediction models to Analyze Titanic Survival Programming using SAS Programming and R.
Ogive Analytics
Sep 2016 - Sep 2019 (3 years)
Junior Statistician
I'm co founder and Junior Statistician at Ogive Analytics.
My responsibility includes analyzing data of
foreign and local clients and writing analysis
report.
My responsibility includes analyzing data of
foreign and local clients and writing analysis
report.
Add some compelling projects here to demonstrate your experience
Abohawa
Mar 2016 - Apr 2016
Abohawa A weather desktop application using openweather api. This application is a project for CSE 298 Object Oriented Programming Language Lab . Programming Language is Java. I have use gson and jsonobject library for json parsing. Using this you can get weather of any location and weather history . A java thread is used to fetch data in the background from website.
How to live Happy Married Life based on Data? Write a Data Science Blog Post
Aug 2020 - Aug 2020
I was interested to analyse this data set to find out what set apart the happily married and divorced couples. In this project I tried to answer the following questions using Divorce Predictors data:
Is there a significant difference between Happily Married and Divorced couples?
What are the most agreed and disagreed things between the couples?
What couples need to focus most to prevent divorce?
How accurately we can predict a future divorce?
Conclusion:
1. There exists a significant difference between married and divorced couples in all the topics of the scale.
2. Divorced and married couple’s top 5 disagreed topics were discussion, humiliating during the discussion, insulting during the discussion, sudden discussion, breaking calm during the discussion.
On the other hand, the top 5 most similar opinionated topics were having time at home for partners, acting like strangers in terms of sharing environment at home. Married couples agreed on average they have more time at home and act less like strangers about family and environment than divorced couples.
The other two topics where married couples were neutral but divorced couples agreed that they mostly stayed silent and felt right in their discussion.
Based on this we can say that married couples are more careful about their discussion, acts less like strangers in terms of sharing environment at home, and gives more time to their partners.
3. Divorced couples and married couples top 10 deciding questions we can see divorced couples and married couples gave opposite answers.
4. Using 70% data as training and 30% data logistic regression model performs best and it can 98.03% accurately predict divorce between couples.
Article Link:
https://medium.com/@ranamahmud/how-to-live-happy-married-life-based-on-data-ebd2d3383aa2
Is there a significant difference between Happily Married and Divorced couples?
What are the most agreed and disagreed things between the couples?
What couples need to focus most to prevent divorce?
How accurately we can predict a future divorce?
Conclusion:
1. There exists a significant difference between married and divorced couples in all the topics of the scale.
2. Divorced and married couple’s top 5 disagreed topics were discussion, humiliating during the discussion, insulting during the discussion, sudden discussion, breaking calm during the discussion.
On the other hand, the top 5 most similar opinionated topics were having time at home for partners, acting like strangers in terms of sharing environment at home. Married couples agreed on average they have more time at home and act less like strangers about family and environment than divorced couples.
The other two topics where married couples were neutral but divorced couples agreed that they mostly stayed silent and felt right in their discussion.
Based on this we can say that married couples are more careful about their discussion, acts less like strangers in terms of sharing environment at home, and gives more time to their partners.
3. Divorced couples and married couples top 10 deciding questions we can see divorced couples and married couples gave opposite answers.
4. Using 70% data as training and 30% data logistic regression model performs best and it can 98.03% accurately predict divorce between couples.
Article Link:
https://medium.com/@ranamahmud/how-to-live-happy-married-life-based-on-data-ebd2d3383aa2
Flashlight Android flashlight application
May 2016 - May 2016
Android flashlight application .
This section lets you add any degrees or diplomas you have earned.
freeCodeCamp
Full Stack Web Development Certification, Computer Software Engineering
Dec 2014 - Dec 2017
Udacity
Data Scientist Nanodegree, Data Science
Dec 2018 - Dec 2019
Shahjalal University of Science and Technology
Master's degree, Statistics
Dec 2017 - Dec 2018
Shahjalal University of Science and Technology
Bachelor’s Degree, Statistics,2nd Major in Computer Science and Engineering
Dec 2012 - Dec 2016
Tableau 10: Mastering Calculations
Dec 2019
Learning Data Governance
Jun 2019
Creating Interactive Presentations with Shiny and R
May 2019