Although I am a full stack web developer,backend and server side development is my
speciality.During the years I have woked on several projects,some are University
related projects and some are of personal interests.
NiceCloud, an ICT/telecom company of Netherlands provide telecom solutions to their clients (office365,Laptops, mobiles etc). NiceHub will handle the communications between the users (sales/tech) and the various external systems (Office365, IRMA, Techdata and Autodesk)
It is basically a motorhome management and care system. The project is built on laravel in the back-end and for front-end we are using flutter.The project is in staging state now. It will have both web and mobile version for Android and IOS
"CHT" - a complain handling tool of GrameenPhone LTD. Basically it is a software to accept, categorize and track customer complaints from initiation through resolution.
"OneGP" - an employee services management system of GrameenPhone LTD.
A human resource management system that has been developed using laravel.The project offers some flexible
options like adding
custom language by the user, adding gates-policies or role based access of resources
to a particular user,
in app and mail notification to the user and many more...
HRM
A total hospital management app that replaces existing manual paper based system.
The system includes doctor, patient, ambulance, hospital, blood banks etc module
and offers different functionalities based on their role.
Online
Hospital
A simple rest api to get data from the server that returns data in JSON format.The
project is done using Spark-a simple java micro framework.The code is well
documented.So you can have a look to find out more.....
Rest API
I have done some interesting machine learning projects till date.My expertise is
basically on NLP.Analysing sentiments from textual data and classifying
texts/comments are some of the many.
The project Play
Store review analysis is a sentiment analysis project that was intended to
give a developer some sort of idea about their app.Analysing the sentiment of the
reviews,the developer can differentiate between the postive and negative reviews and
later on can cluster them to find out what people are liking about his/her app and
what functionality needs improvement.
In this project,I have used word embeddings namely word2vec as feature
extractor.This trained word embeddings is then feed to embedding layer.Later,GRU-an
RNN architecture, which is similar to LSTM has been used.You can find the full
details on the above link.