noaimabari

Traffic-Sign-Detection-and-Recognition

Ongoing personal project involving detection and classification of traffic signs from GTSDB(German Traffic Sign Detection Benchmark) dataset using object detection algorithms such as Faster R-CNN.

Reddit_Flair_Detector

Web app created using python’s micro web framework flask which predicts the flair of a reddit post given its url. The project utilizes data science concepts and NLP techniques for extracting, cleaning, processing of text data and performing exploratory data analysis. Machine learning algorithms used for classification.

Twitter-Sentiment-Analysis

Predicting sentiment of a tweet by using NLP techniques to clean data and multinomial naive bayes classifier to perform classification

Face-Mask-Detection

Face mask detection in crowded scenes using Faster R-CNN with an inception v2 base model using TensorFlow. Network trained for 9 hours on TESLA K80 GPU.

Handwritten-Digit-Recognition

Recognizing handwritten digits with the help of deep learning model made using keras. CNN applied to improve feature set and neural networks for classification.

InstaBot

Instagram bot made using selenium. Completely automates the process of using Instagram. BeautifulSoup used for data scraping wherever required.

Airline-Booking-Management-System

web app enabling users to book flight tickets and perform other search operations (relational database concepts)

BuzzyGame

C++ Game Development using SFML

Model_Pruning_Splines_Visualization

BuzzyBowl

C++ 3D Simulation using OpenGL

datasciencecoursera

answer to ques 2 of course project

datasharing

The Leek group guide to data sharing

default

Face-Detection

Face Detection in images and live video streams using OpenCV

hello_world

A new repository to learn more about how to use git hub

Know-Your-Intent

State of the Art results in Intent Classification using Sematic Hashing for three datasets: AskUbuntu, Chatbot and WebApplication.

MELD

MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversation

noaimabari.github.io

practice2

Project-Text-Classification

Analysed a dataset containing 20,000 text messages from 20 different newsgroups. Cleaned the data, processed the words and formed the vocabulary. Implemented Multinomial naive bayes from scratch for classification of the messages into the 20 different classes. Compared the results with those obtained using the inbuilt sklearn multinomial naive bayes classifier. Achieved an accuracy of nearly 70%. Python libraries used: sklearn, nltk, matplotlib, numpy.

repo2

this is again a practice repo

Start-Up-Funding-Analysis

Analysed a data set containing information about funding received by various start ups by using Python and its powerful scientific computing and visualization libraries.

test-repository

this is a practice repo

VoiceProcessing

Voice Processing using librosa