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customer-churn-analysis---ml-project

Customers in the telecom industry can choose from a variety of service providers and actively switch from one to the next. With the help of ML classification algorithms, we are going to predict the Churn

customer-segmentation--ml-project

This project involves clustering analysis on a dataset of active credit card holders to segment customers based on their usage behavior. By applying clustering algorithms and techniques such as scaling, dimensionality reduction, and hyperparameter tuning, personalized recommendations for financial products are generated.

e-commerce-sales-dashboard-using-power-bi

Welcome to E-commerce Sales Dashboard! 🚀 We uses time series analysis to deliver sales forecasts and valuable insights. This dashboard feature interactive visualizations, allowing deep exploration of key metrics.

housing-price-prediction-using-machine-learning

This project utilizes regression machine learning techniques, specifically the XGBoost model, to predict housing prices. The XGBoost algorithm excels in handling complex datasets, making it an ideal choice for accurately forecasting housing prices. This GitHub repository showcases the implementation and results using predictive model

hr-analytics-dashboard-using-power-bi

Explore our HR Analytics Dashboard, a powerful Power BI project designed for HR managers and leaders. Analyzed essential KPIs such as Employee Count, Attrition Rate, and Job Satisfaction across various demographics. Our intuitive visualizations, including Lollipop, Pie, Bar, and Donut charts, empower targeted decision-making.

mall-customer-data-clustering

This project performs customer segmentation analysis for a mall dataset using machine learning techniques in Python. It aims to understand customer behavior and preferences based on features such as age, gender, average income, and spending score.

mlproject

most-streamed-spotify-songs-2023-analysis-

Dive into the rhythm of 2023's chart-toppers with Spotify Insights! 🎵 We explore music's core, dissecting beats, danceability, and energy. Analyzing streams by track and artist, we uncover musical trends and unveil the secrets behind hits. 📊🎶

netflix-eda

After the lockdown , ott platforms got a big boost , and one such popular streaming platform is Netflix. To better understand user behavior and content popularity, we collected a dataset with information like movie name, cast, type, and ratings. Using data mining techniques, we were able to evaluate patterns and extract relevant information from it

newproject

nyc-311-customer-service-requests-analysis

Performed a service request data analysis of New York City 311 calls. Focused on the data wrangling techniques to understand the pattern in the data and also visualize the major complaint types.

revenue-insights-in-hospitality-using-power-bi

This Power BI project analyzes 3 months' data, empowering stakeholders with key metrics: RevPAR, ADR, DBRN, DSRN, Realization %, and Occupancy %. Diving into seamless steps: data import, transformation, measure creation, and dynamic dashboard setup. Transforming the decision-making today! 🚀

road-accident-dashboard-excel-project

This repository hosts the codebase for a comprehensive Road Dashboard designed for the years 2021 and 2022. The dashboard provides valuable insights into road safety metrics, aiding in understanding and analyzing various aspects of road accidents and casualties. Developed for our client, this dashboard aims to enhance awareness and decision-making

sonar-rock-vs-mine-prediction-using-python

This project involves the classification of sonar signals into two categories, rocks or mines, using Logistic Regression algorithm.