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anonymous_course_review_site

astro_mania

bit_manipulation

blackjack

budget_tracker_web_app

cnn-transformer-for-eeg

connect_4

contact_managment_system

crazy_8_game

flight-ticket_management_system

graph_neural_networks_for_eeg

image-classification-vgg16

This project modifies the classic VGG16 architecture to classify images into four distinct categories with high accuracy. It incorporates data augmentation, dynamic learning rate adjustments, and comprehensive performance evaluation using accuracy metrics and confusion matrices. Built with PyTorch and supported by a suite of powerful libraries

iris_flower_species_predictor_streamlit_deployment

Predicts Iris species with 100% aacuracy. It's deployed on streamlit.

lstm_cnn-for-eeg

ml-driven-clv-prediction

This project predicts Customer Lifetime Value (CLV) for e-commerce. It aims at forecasting the revenue a business can expect from a customer over time. I did an explatory analysis. From Linear Regression to Neural Networks, explore how different models perform in predicting CLV.

nlp-imdb-sentiment-analysis

old_portfolio

pern-fullstack-budget_tracker

real-time-object-detection

Real-time object detection system utilizing the SSD MobileNet V2 FPNLite 320x320 model for high-speed, efficient recognition.

spotify_stock_analysis

This is an in-depth exploratory data analysis of Spotify's stock performance from January 1, 2018, to the present. Utilizing Python and a robust set of libraries, this project examines trends, volatility, and external influences on Spotify's stocks using data from Yahoo Finance. From trend analysis and volatility exploration to predictive modeling.

task_manager

terms_and_conditions-sumarizer

tetris_rush

travel_planner

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