Osama Ahmed Tahir's Projects
Being an Astronaut was one my childhood dream but unfortunately, I landed with a career in Software Engineering. To bring one instance of my childhood dream to reality, I would be making a game which would send the user to space where he must survive from asteroid and ruthless alien. For the user to get back to his home planet, he needs to cover great distance with number of enemies on each edge. As the user proceeds, he would be gaining points as reward and incentives. This game is fully developed on C# and Splash-kit.
A system which is entirely made to provide an Augmented assistance to the customers , the customer could be an either patient who is coming to the hospital for the first time , or a student who is coming to the university for the first time.
An automation framework for rapidly and consistently deploying production-ready DLT platforms
Having a data-set of over 80,000 games and then use that information to train a Linear Regression model and a Random Forest Regressor to make a prediction based on those games. The scope extends to using further non-linear Regressors which might have better accuracy of the prediction This prediction information comes to handy if we wanted to know the kind of games people liked and get more higher ratings
Welcome to the Bot Framework samples repository. Here you will find task-focused samples in C#, JavaScript and TypeScript to help you get started with the Bot Framework SDK!
Machine learning (ML) has been recently introduced to develop prognostic classification models that can be used to predict outcomes in individual cancer patients. Here, we report the significance of an ML-based decision support system while using the dataset from UCI website and using Machine Learning Models like KNN and Support Vector Machine to predict the cancerous cell.
Multi-image viewer with synchronized zoom and sliding overlays. Drag, drop, and instantly compare multiple images side by side. Very open source.
content for Udacity's cloud developer nanodegree
This application is still in production. The application is entirely made upon NodeJs along with React.It consist of finding a suitable course for the any of the student based upon his requirement.
Fraud detection is a complex issue that requires a substantial amount of planning before throwing machine learning algorithms at it. I was able to get data-set from Kaggle Competition and use different techniques of Machine Learning which includes Local Outlier Factor and Isolation Forest to detect the outliers.
There are multiple applications which includes the methods of clustering , K-mean , Word Cloud , Randomn Forest, Ordered Weighted Average and PCA. Each of the application can be hosted on the server and can be run as per requirement.
A Final Year Project
React frontend boilerplate
Deep Learning Recommendation System Research
AWS Deep Racer
Fake news data downloaded from Kaggle regarding fake news. Applied pre-processing steps on the textual columns such as stopwords removal, tokenization, lemmatization, etc. Performed EDA on the dataset such as Emotion detection, Hate Speech detection, frequency of words, bi-grams, etc and applied BERT model for word embedding.Used BERT embeddings to visualize it through T-SNE plot.
This project contains Django project having containerize environment. It has all the dependencies the application needs to run, making it easy to deploy app on any server.
JWT based authentication service by Django
A simple todo application that uses React on the frontend and Django on the backend with sqlite3 database. I have followed this tutorial to make the application https://www.geeksforgeeks.org/integrating-django-with-reactjs-using-django-rest-framework/
This project is an implementation example for reset password of django
A complete docker package for django which is easy to understand and can be deployed anywhere(supports Data Science related libraries like numpy, scipy etc).
This source code represents data visualization using d3.js, dc.js, node.js and mongodb. A dashboard has been established which shows the analysis of Student Donation with respect to grades and states. The data has been represented by different graphs with multiple options for the users to select from.