gridsearch-cv

The rapid growth of social media has led to an increase in user-generated content, making platforms like Twitter a major medium for public communication. However, along with positive engagement, there has also been a surge in hate speech, offensive language, and abusive content. This project aims to address this challenge by developing a ML program

The main objective of this project is predicting rainfall for each day of the year. For this project i used pyspark, and Machine Learning

A churn bank model that classify the customers if they stop dealing with the bank or not

ML classification pipeline predicting drinking water safety across 3,276 samples - compares Logistic Regression, Random Forest, and tuned RF (GridSearchCV) on 9 physicochemical features with class imbalance handling and missing value imputation.

A Streamlit-based machine learning app that predicts the likelihood of a credit card customer defaulting next month.