Machine learning model for Credit Card Fraud Detection

Explore the vast field of Natural Language Processing (NLP) with our comprehensive toolkit. From text preprocessing to advanced sentiment analysis and language modeling, this repository provides a range of tools and algorithms to empower your NLP projects. Dive into state-of-the-art techniques and resources curated to enhance your understanding.

A machine learning project designed to predict the likelihood of heart disease based on a set of health indicators.

A decision tree classification model based on bank marketing data

The Email Spam Model project aims to build a machine learning model that can classify emails as spam or not spam (ham). The project uses various text processing techniques and machine learning algorithms to achieve accurate predictions.

The motive of this project is to find out the customer satisfaction of some residential hotels of Dhaka.

This project focuses on predicting customer churn in the telecom industry using machine learning techniques. The model is trained to identify factors that influence customer retention and accurately predict whether a customer is likely to stay or leave.

This model can predict whether an email is spam or not. The logistic regression machine learning algorithm is used to train this model.

This code evaluates the performance of a logistic regression model on age prediction using various features to predict a binary target variable, calculating metrics to determine the performance. It evaluates the comparison, identifies favorable features, and visualizes the ROC-AUC curve to determine the best model performance.

This project develops an activity recognition model for a mobile fitness app using statistical analysis and machine learning. By processing smartphone sensor data, it extracts features to train models that accurately recognize user activities.

This Project is based on Machine Learning which uses Logistic Regression model for predicting whether the object detected by Submarine is Rock or Mine

This repo desribes bulding a decision tree to predict customer churn in a given organisation

This github repositiory contains the Flight Price Prediction project aims to develop a machine learning model to predict flight ticket prices based on various factors such as departure and arrival locations, dates, airlines, and other relevant features.

OilyGiant mining company finding the best place for 200 new well points, As an Data Scientist we're creating a model who can choose the best 200 point by profit and risk.

Bank Beta Company focus on retain existing customers, our task is to create a model that predicts whether or not a customer will leave the bank soon.

Megaline company wants to develop a model that can analyze consumer behavior and recommend one of Megaline's two new plans: Smart or Ultra. In this classification task, we need to develop a model that is able to choose the right package

This is the Data Mining Project for predicting the student's grade before the final and Mid-2 examination. I use Python and Jupyter Notebook for this Project.

1) Pima_Indians_Diabetes_dataset: 83.11% accuracy. 2) Using ScanPy for gene expressions in scRNA sequencing. 3) Using traditional clustering on RNA dataset 4) Stroke Prediction 95% accuracy on test

Spam Mail Prediction using Machine Learning