Mihiru Lakshitha Silva's repositories
Car-selling-platform
Car Selling Platform: A Django-based web app for users to list, buy, and bid on vehicles. Includes user authentication, CRUD operations, and a bidding system.
206066G-Assignment-02
Created a calculator for the assignment using git branches
206064A-My-project
This is my repo of given assignment under business application development module
my-project1
add multiplication function
Credit-Risk-Analysis-classification-project
EDA & Predictive modeling on loan dataset to identify the risk customers and avoid unnecessary loseses
AI-University-attendence-mark-system
The AI University attendance marking system is an automated system that uses AI algorithms to mark attendance for students in universities.
Student-s-Focus-Tracking-System
The Student's Focus Tracking System is a system that employs deep learning algorithms to analyze students' facial expressions, body language, and vocal cues during lectures. The system utilizes sensors like cameras or microphones to track students' focus levels, providing real-time feedback to professors.
Skin-Diseases-detector-Mobile-application
End to End Deep learning based Skin Diseases predictor. Application has the ability to recognize 20 types of Skin Diseases and provide essential recommandations.
Project-01-Vehicle-Price-Prediction
The price of a car depends on a lot of factors like the goodwill of the brand of the car, features of the car, horsepower and the mileage it gives and many more. Car price prediction is one of the major research areas in machine learning. In this project, I am going to Apply Data science techniques to Undertand the core features of the data and build a Machine Learning and deep learning models to predict the car sale price. Projrct content and sections - Business problem Identification - Explorative Data analytics - Data preparation & Cleaning - Data Visualization - Data Understanding and Interprining - Feature selection & Feature Enginering - Understand the Features - Select core Features - Handling Imbalance Data - Encode the catagorical data - Sacle down the data (Apply one hot encoding) - Build MAchine learning models - Split The data - Build the model - Evaluvate the ML model accuracy (1st round) - hyperparameter tuning - Evaluate the ML model accuracy (2st round) - Build Deep Learning Model - Evaluate the DL model accuracy
Project-0_customer-churn
customer churn prediction
Mihiru-Lakshitha
Config files for my GitHub profile.