Pinned Repositories
ML_through_project_based_learning
A project-based roadmap for mastering machine learning, covering essential concepts like supervised and unsupervised learning, deep learning, NLP, and model deployment. Each phase includes hands-on projects to build practical skills and a strong portfolio.
Heart_Disease_Prediction
This project focuses on predicting heart disease using classification models like Random Forest, Gradient Boosting, and XGBoost. A Streamlit web app is built to allow users to input clinical data and receive predictions about their likelihood of heart disease.
Game-Agent
Image-Classification
This project implements a Convolutional Neural Network (CNN) to classify images from the CIFAR-10 dataset, which consists of 60,000 32x32 color images across 10 classes: airplane, automobile, bird, cat, deer, dog, frog, horse, ship, and truck.
Sentiment-Analysis-on-Text-Data
This project aims to classify IMDb movie reviews as positive or negative using a Bidirectional LSTM model.
Amazon_clone
Call_Centre_power_BI_Dashboard
Create a dashboard in Power BI to visualize relevant KPIs and metrics that will help the call center manager understand trends.
Credit_Card_Fraud_Detection
This project aims to detect fraudulent transactions in a dataset using machine learning models like Logistic Regression and Decision Tree. The dataset is highly imbalanced, and techniques like SMOTE are used to balance it.
Customer_Churn_Analysis_Power_BI_Dashboard
The Customer Churn Analysis Power BI Dashboard provides businesses with powerful insights into customer churn patterns. By analyzing key factors like customer demographics, service usage, and billing, this project helps identify high-risk customers and develop strategies to improve retention.
Customer_Churn_Prediction
This project aims to build a predictive model that helps identify customers at risk of churning (leaving the service) in a telecommunications company. By leveraging machine learning techniques, we can help businesses take preemptive actions to retain valuable customers and reduce churn rates.
SunnyBibyan's Repositories
SunnyBibyan/ML_through_project_based_learning
A project-based roadmap for mastering machine learning, covering essential concepts like supervised and unsupervised learning, deep learning, NLP, and model deployment. Each phase includes hands-on projects to build practical skills and a strong portfolio.
SunnyBibyan/Amazon_clone
SunnyBibyan/Call_Centre_power_BI_Dashboard
Create a dashboard in Power BI to visualize relevant KPIs and metrics that will help the call center manager understand trends.
SunnyBibyan/Credit_Card_Fraud_Detection
This project aims to detect fraudulent transactions in a dataset using machine learning models like Logistic Regression and Decision Tree. The dataset is highly imbalanced, and techniques like SMOTE are used to balance it.
SunnyBibyan/Customer_Churn_Analysis_Power_BI_Dashboard
The Customer Churn Analysis Power BI Dashboard provides businesses with powerful insights into customer churn patterns. By analyzing key factors like customer demographics, service usage, and billing, this project helps identify high-risk customers and develop strategies to improve retention.
SunnyBibyan/Customer_Churn_Prediction
This project aims to build a predictive model that helps identify customers at risk of churning (leaving the service) in a telecommunications company. By leveraging machine learning techniques, we can help businesses take preemptive actions to retain valuable customers and reduce churn rates.
SunnyBibyan/Diversity_-_Inclusion_Power_BI_Dashboard
Create visualizations to represent HR data, particularly focusing on gender-related KPIs. Identify and discuss potential root causes for the slow progress in achieving gender balance at the executive management level.
SunnyBibyan/Exploratory-Data-Analysis-EDA
Welcome to the Titanic Dataset - Exploratory Data Analysis (EDA) project repository! This project aims to uncover insights from the Titanic dataset using Python and Jupyter Notebook. By analyzing key variables such as age, gender, and class, we aim to visualize relationships between passenger characteristics and survival rates.
SunnyBibyan/Heart_Disease_Prediction
This project focuses on predicting heart disease using classification models like Random Forest, Gradient Boosting, and XGBoost. A Streamlit web app is built to allow users to input clinical data and receive predictions about their likelihood of heart disease.
SunnyBibyan/Marketing_Campaign_Analysis_Power_BI_Dashboard
Campaign Performance Analysis This project analyzes the performance of Spring, Summer, and Fall marketing campaigns, revealing key insights and actionable recommendations.
SunnyBibyan/Random_Data_Generation
A project that generates a dataset using various statistical distributions (Normal, Uniform, Exponential, Random Integers, and Binomial) and performs data analysis. Includes visualizations and an option to export the data as a CSV file.
SunnyBibyan/SuNnY_BiByAn_Portfolio_website
Welcome to the SuNnY_BiByAn Portfolio Website repository! This project showcases my personal portfolio, highlighting my skills, projects, and professional services. The live website is hosted here.
SunnyBibyan/sunnybibyan.github.io
Welcome to my personal website repository! This platform showcases everything related to me 🌈. Here, you’ll find links to my various projects, as well as information about my background, experience, and interests. The live website is hosted on GitHub Pages
SunnyBibyan/Deploy-a-Sentiment-Analysis-Model
SunnyBibyan/Game-Agent
SunnyBibyan/Handwritten-Digit-Recognition-Neural-Networks-
SunnyBibyan/Handwritten-Digit-Recognition-PCA-K-Means-
This repository features a project on handwritten digit recognition using PCA for dimensionality reduction and K-Means Clustering for grouping the MNIST dataset. t-SNE is employed to visualize the clustering results in 2D.
SunnyBibyan/Image-Classification
This project implements a Convolutional Neural Network (CNN) to classify images from the CIFAR-10 dataset, which consists of 60,000 32x32 color images across 10 classes: airplane, automobile, bird, cat, deer, dog, frog, horse, ship, and truck.
SunnyBibyan/Sentiment-Analysis-on-Text-Data
This project aims to classify IMDb movie reviews as positive or negative using a Bidirectional LSTM model.
SunnyBibyan/Stock-Price-Prediction
SunnyBibyan/Text-Summarization-or-Translation-