Pinned Repositories
Beginner-MLOps-Project-Brazilian-E-Commerce
This project uses the Brazilian E-Commerce Public Dataset by Olist to analyze customer behavior and sales trends. Utilizing ZenML, I implemented an MLOps workflow for data preprocessing, model training, and deployment, focusing on scalability and performance monitoring.
Bike-Share-prediction
This project uses machine learning to predict bike-sharing demand, helping companies optimize fleet management, reduce costs, and improve customer satisfaction. A web application will provide accessible real-time predictions to support data-driven decisions.
Book-Recommendation-System
Created a book recommendation system that providing personalized book suggestions based on user ratings and book features. It demonstrates different types of recommendation algorithms and evaluates their performance
Churn-Rate-Analysis
Handling-Imbalance-Data
This repository showcases techniques for handling imbalanced datasets in machine learning, where one class dominates, leading to biased models. It demonstrates methods like oversampling, undersampling, and SMOTETomek to address this issue effectively.
Handling-Missing-Values
This notebook covers practical techniques for handling missing data in both numerical and categorical features, helping improve model performance. Suitable for both beginners and experienced data scientists.
List-of-companies-in-India
Python-for-Data-Science-Mastering-Essentials
This repository provides in-depth notebooks covering essential topics
TITANIC-solution
This repository contains a Jupyter notebook that demonstrates a comprehensive data analysis process and machine learning techniques to predict the survival of passengers on the Titanic. This project is intended for beginners who are looking to get started with data analysis and machine learning.
US-Visa-Approval-Prediction-MLOPs-Project
This project predicts US visa approval using machine learning based on factors like education, job experience, and company details. It integrates MongoDB for data storage and Evidently for model evaluation. The project is structured with modular components for data ingestion, transformation, validation, and model training.
RanaSanga85's Repositories
RanaSanga85/Beginner-MLOps-Project-Brazilian-E-Commerce
This project uses the Brazilian E-Commerce Public Dataset by Olist to analyze customer behavior and sales trends. Utilizing ZenML, I implemented an MLOps workflow for data preprocessing, model training, and deployment, focusing on scalability and performance monitoring.
RanaSanga85/Bike-Share-prediction
This project uses machine learning to predict bike-sharing demand, helping companies optimize fleet management, reduce costs, and improve customer satisfaction. A web application will provide accessible real-time predictions to support data-driven decisions.
RanaSanga85/Book-Recommendation-System
Created a book recommendation system that providing personalized book suggestions based on user ratings and book features. It demonstrates different types of recommendation algorithms and evaluates their performance
RanaSanga85/Handling-Imbalance-Data
This repository showcases techniques for handling imbalanced datasets in machine learning, where one class dominates, leading to biased models. It demonstrates methods like oversampling, undersampling, and SMOTETomek to address this issue effectively.
RanaSanga85/Handling-Missing-Values
This notebook covers practical techniques for handling missing data in both numerical and categorical features, helping improve model performance. Suitable for both beginners and experienced data scientists.
RanaSanga85/List-of-companies-in-India
RanaSanga85/Python-for-Data-Science-Mastering-Essentials
This repository provides in-depth notebooks covering essential topics
RanaSanga85/TITANIC-solution
This repository contains a Jupyter notebook that demonstrates a comprehensive data analysis process and machine learning techniques to predict the survival of passengers on the Titanic. This project is intended for beginners who are looking to get started with data analysis and machine learning.
RanaSanga85/US-Visa-Approval-Prediction-MLOPs-Project
This project predicts US visa approval using machine learning based on factors like education, job experience, and company details. It integrates MongoDB for data storage and Evidently for model evaluation. The project is structured with modular components for data ingestion, transformation, validation, and model training.
RanaSanga85/Churn-Rate-Analysis
RanaSanga85/RanaSanga85
Config files for my GitHub profile.