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5201-login-bem-jslint's Introduction

Hi there ๐Ÿ‘‹

Hi, my name is Jalal, and this readme file provides a categorical summarization of some of the representative repos I have on my Github account. You can also visit my linkedin profile to learn more about my background.

Projects which I completed on algorithm design for computational problems can be accessed from my Google Scholar profile. One of my best work had been the design of Triangular Code in which I designed a coding schme with encoding-decoding computational complexities of O(k log k) within minimal overhead, k is the number of data packets. My closest competitor, Raptor code, US patented and owned by Qualcomm has a complexity of O(k1.5).

Algorithms and Data Structure

  • Algorithms and Data Structure - In this single repo, I have added my source code (mostly in C++) for various problems in Computer Science which can be solved using efficient Algorithms and Data Structure. Solution for each of the problems is in a subfolder, with its own Readme file.

Front-end

Back-end

  • Twitter and Google Map APIs integration - Integration of multiple API (Application Programming Interface) so that user can see on map the location of user posting tweets containing a keyword. PHP and Javascript was used to send request to the Twitter and Google Map APIs respectively.
  • Ticket Support System XML DOM - Implementation of a ticket support system, with two different user privilage, admin, and client. XML was used to store data, and PHP DOM was used to interact with the XML document.
  • Medical Clinic website, responsive - Group project in which my team designed and developed the website for a medical clinic using PHP and MySQL database. The content on the website was dynamic and database driven

Database

  • Database design on Access - Designed an ERD and created its database on Microsoft Access. Forms and reports were created for end-users to interact with the database tables.
  • MySQL Queries - SQL queries to extract information across multiple connected tables in a database.

Data Analytics, Machine Learning

  • Customer Segmentation - Segmentation of customers profile based on clustering, and then perfroming classification to identify value conscious customers. Python Anaconda was used to perform the analysis.
  • Data ETL and Visualization - Auditing and cleaning structured data using SAS, performing exploratory data analysis (EDA) and then coming up with visualization reports using Tableau.
  • Class balance and imbalance models - Worked on a business problem using classification (determining whether company would be able to sell procured obsolete electronic components) with balance and imbalance classes in the dataset using Python Anaconda.

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