Pinned Repositories
Anonymous_Course_Review_Site
Astro_Mania
Bit_Manipulation
Blackjack
Budget_Tracker_Web_App
CNN-Transformer-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
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.
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.
Yonas650's Repositories
Yonas650/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
Yonas650/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.
Yonas650/Real-Time-Object-Detection
Real-time object detection system utilizing the SSD MobileNet V2 FPNLite 320x320 model for high-speed, efficient recognition.
Yonas650/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.
Yonas650/Anonymous_Course_Review_Site
Yonas650/Astro_Mania
Yonas650/Bit_Manipulation
Yonas650/Blackjack
Yonas650/Budget_Tracker_Web_App
Yonas650/CNN-Transformer-for-EEG
Yonas650/Connect_4
Yonas650/Contact_Managment_system
Yonas650/Crazy_8_Game
Yonas650/Flight-Ticket_Management_System
Yonas650/Iris_Flower_Species_Predictor_Streamlit_Deployment
Predicts Iris species with 100% aacuracy. It's deployed on streamlit.
Yonas650/LSTM_CNN-for-EEG
Yonas650/NLP-IMDb-Sentiment-Analysis
Yonas650/old_portfolio
Yonas650/pern-fullstack-Budget_tracker
Yonas650/Task_Manager
Yonas650/Terms_and_Conditions-Sumarizer
Yonas650/Tetris_Rush
Yonas650/Travel_planner
Yonas650/Yonas650.github.io