VamsiKrishna Surisetti's repositories
Customer-Segmentation-Sentiment-Analysis-and-Predictive-Modelling.
This project carefully studies the customer reviews of a airline company, around 10,000+ reviews are collected through webscrapping and and by sentiment analysis captured the expierence of the customers. And based on that designed a Machine learning algorithm which is a random forest classifier to predict customers who are likely to book seats.
RetailData-Analytics-Nexus
Revolutionize retail with RetailData Analytics Nexus. This cutting-edge platform intertwines data, offering strategic insights for optimal retail performance. Elevate decision-making, harness market dynamics, and chart a course to success in just a glance.
Big-Data-Analysis-in-Social-Media-sphere
In the dynamic landscape of e-commerce media platforms, the ability to understand and cater to individual customer needs is paramount for success. This project aims to implement predictive customer segmentation techniques to enhance personalized marketing strategies and product recommendations.
Customer_churn_prediction
The objective of this project is to develop an accurate and robust customer churn prediction model to forecast the likelihood of customers leaving a service or product. Additionally, the project aims to propose effective retention strategies based on the insights gained from the predictive model.
NIGERIAN_FOODPRICE_PREDICTION
Implemented a comprehensive data analysis initiative leveraging machine learning techniques and Python programming to examine historical food price data in Nigeria. This project aimed to forecast future trends and provide valuable insights for both consumers and stakeholders in the food industry.
Olympic_medal_predictor
Employing regression modeling, this project predicts a country's medals in sports events based on historical data. Cleaned and prepared datasets are used to train and optimize the model. Insights gained from the predictive analysis aid athletes and stakeholders in strategizing for upcoming competitions.
T_20_DATA_ANALYTICS
This project employs data analytics to construct a T20 cricket team that consistently scores 180+ runs and defends against scores below 150. By analyzing player performance and historical data, we aim to strategically form a team capable of securing victories in the fiercely competitive world of T20 cricket.
project-walkthroughs
Data science, machine learning, and web development project code for https://www.youtube.com/c/Dataquestio .