juveria2932
Navigating the peaks and pitfalls of AI, ML and DS while balancing between the excitement of discoveries and the reality of debugging. Let's connect!
Pinned Repositories
d92a4cb6-0ac1-46e2-8163-a3013f48976f
https://sonarcloud.io/summary/overall?id=examly-test_d92a4cb6-0ac1-46e2-8163-a3013f48976f
Employee-Attrition-Armor
Employee AttritionArmor is a data-driven, machine learning project that generates valuable insights and predicts the attrition of employees in an organization.
Hoops-or-Oops-AR
Augmented Reality game developed on Spark AR Platform. Deployed as a filter on Instagram and Facebook, resembling a basketball game.
Sales-Prediction-with-EDA
This project builds a sales prediction model using machine learning, emphasizing TV, radio, and newspaper advertising expenditures. By analyzing historical data, the model forecasts future sales with a random forest algorithm, aiding businesses in optimizing marketing strategies and anticipating sales outcomes.
Student-placement-predictor-application
Introducing our Student Placement Predictor app: Powered by K-Nearest Neighbors (KNN) machine learning model, it evaluates student placement probabilities based on key metrics like CGPA, IQ, and profile score. Integrating historical placement data, it empowers students & recruiters by providing insights to enhance placement strategies and outcomes.
yolov8-waste-classification-streamlitapp
The Waste Classification System is a project that focuses on accurately classifying waste into six different types: cardboard, paper, plastic, metal, glass, and biodegradable using YOLOv8 model. By analyzing waste images, the system provides users with the correct waste category, facilitating effective waste management and recycling efforts.
Waste-Classification-using-YOLOv8
The Waste Classification System is a project that focuses on accurately classifying waste into six different types: cardboard, paper, plastic, metal, glass, and biodegradable using YOLOv8 model. By analyzing waste images, the system provides users with the correct waste category, facilitating effective waste management and recycling efforts.
juveria2932's Repositories
juveria2932/yolov8-waste-classification-streamlitapp
The Waste Classification System is a project that focuses on accurately classifying waste into six different types: cardboard, paper, plastic, metal, glass, and biodegradable using YOLOv8 model. By analyzing waste images, the system provides users with the correct waste category, facilitating effective waste management and recycling efforts.
juveria2932/Employee-Attrition-Armor
Employee AttritionArmor is a data-driven, machine learning project that generates valuable insights and predicts the attrition of employees in an organization.
juveria2932/Hoops-or-Oops-AR
Augmented Reality game developed on Spark AR Platform. Deployed as a filter on Instagram and Facebook, resembling a basketball game.
juveria2932/Sales-Prediction-with-EDA
This project builds a sales prediction model using machine learning, emphasizing TV, radio, and newspaper advertising expenditures. By analyzing historical data, the model forecasts future sales with a random forest algorithm, aiding businesses in optimizing marketing strategies and anticipating sales outcomes.
juveria2932/Student-placement-predictor-application
Introducing our Student Placement Predictor app: Powered by K-Nearest Neighbors (KNN) machine learning model, it evaluates student placement probabilities based on key metrics like CGPA, IQ, and profile score. Integrating historical placement data, it empowers students & recruiters by providing insights to enhance placement strategies and outcomes.